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  • 1. Acín, Antonio
    et al.
    Pironio, Stefano
    Vértesi, Tamás
    Wittek, Peter
    University of Borås, Faculty of Librarianship, Information, Education and IT.
    Optimal randomness certification from one entangled bit2016In: Physical Review A. Atomic, Molecular, and Optical Physics, ISSN 1050-2947, E-ISSN 1094-1622, Vol. 93, no 4Article in journal (Refereed)
    Abstract [en]

    By performing local projective measurements on a two-qubit entangled state one can certify in a device-independent way up to one bit of randomness. We show here that general measurements, defined by positive-operator-valued measures, can certify up to two bits of randomness, which is the optimal amount of randomness that can be certified from an entangled bit. General measurements thus provide an advantage over projective ones for device-independent randomness certification.

  • 2. Baccari, Flavio
    et al.
    Cavalcanti, Daniel
    Wittek, Peter
    University of Borås, Faculty of Librarianship, Information, Education and IT.
    Acín, Antonio
    Efficient device-independent entanglement detection for multipartite systems2016In: arXiv, article id 1612.08551Article in journal (Other academic)
    Abstract [en]

    Entanglement is one of the most studied properties of quantum mechanics for its application in quantum information protocols. Nevertheless, detecting the presence of entanglement in large multipartite sates keeps being a great challenge both from the theoretical and the experimental point of view. Most of the known methods either have computational costs that scale inefficiently with the number of parties or require more information on the state than what is attainable in every-day experiments. We introduce a new technique for entanglement detection that provides several important advantages in these respects. First, its scales efficiently with the number of parties, thus allowing for application to systems composed by up to few tens of parties. Second, it needs only the knowledge of a subset of all possible measurements on the state, therefore being apt for experimental implementation. Moreover, since it is based on the detection of nonlocality, our method is device-independent. We report several examples of its implementation for well-known multipartite states, showing that the introduced technique has a promising range of applications.

  • 3. Biamonte, Jacob
    et al.
    Wittek, Peter
    University of Borås, Faculty of Librarianship, Information, Education and IT.
    Pancotti, Nicola
    Rebentrost, Patrick
    Wiebe, Nathan
    Lloyd, Seth
    Quantum Machine Learning2016In: arXiv, article id 1611.09347Article in journal (Other academic)
    Abstract [en]

    Recent progress implies that a crossover between machine learning and quantum information processing benefits both fields. Traditional machine learning has dramatically improved the benchmarking and control of experimental quantum computing systems, including adaptive quantum phase estimation and designing quantum computing gates. On the other hand, quantum mechanics offers tantalizing prospects to enhance machine learning, ranging from reduced computational complexity to improved generalization performance. The most notable examples include quantum enhanced algorithms for principal component analysis, quantum support vector machines, and quantum Boltzmann machines. Progress has been rapid, fostered by demonstrations of midsized quantum optimizers which are predicted to soon outperform their classical counterparts. Further, we are witnessing the emergence of a physical theory pinpointing the fundamental and natural limitations of learning. Here we survey the cutting edge of this merger and list several open problems.

  • 4. Calderaro, Luca
    et al.
    Fetter, Alexander L.
    Massignan, Pietro
    Wittek, Peter
    University of Borås, Faculty of Librarianship, Information, Education and IT.
    Vortex dynamics in coherently coupled Bose-Einstein condensates2017In: Physical Review A. Atomic, Molecular, and Optical Physics, ISSN 1050-2947, E-ISSN 1094-1622, Vol. 95, no 2, article id 023605Article in journal (Other academic)
    Abstract [en]

    In classical hydrodynamics with uniform density, vortices move with the local fluid velocity. This description is rewritten in terms of forces arising from the interaction with other vortices. Two such positive straight vortices experience a repulsive interaction and precess in a positive (anticlockwise) sense around their common centroid. A similar picture applies to vortices in a two-component two-dimensional uniform Bose-Einstein condensate (BEC) coherently coupled through rf Rabi fields. Unlike the classical case, however, the rf Rabi coupling induces an attractive interaction and two such vortices with positive signs now rotate in the negative (clockwise) sense. Pairs of counter-rotating vortices are instead found to translate with uniform velocity perpendicular to the line joining their cores. This picture is extended to a single vortex in a two-component trapped BEC. Although two uniform vortex-free components experience familiar Rabi oscillations of particle-number difference, such behavior is absent for a vortex in one component because of the nonuniform vortex phase. Instead the coherent Rabi coupling induces a periodic vorticity transfer between the two components.

  • 5. Curchod, Florian J.
    et al.
    Johansson, Markus
    Augusiak, Remigiusz
    Hoban, Matthew J.
    Wittek, Peter
    Acín, Antonio
    Unbounded randomness certification using sequences of measurements2015In: Physical Review A. Atomic, Molecular, and Optical Physics, ISSN 1050-2947, E-ISSN 1094-1622, Vol. 95, no 2Article in journal (Refereed)
  • 6.
    Darányi, Sandor
    et al.
    University of Borås, Swedish School of Library and Information Science.
    Wittek, Peter
    University of Borås, Swedish School of Library and Information Science.
    Dobreva, Milena
    Toward a 5M Model of Digital Libraries2010Conference paper (Refereed)
    Abstract [en]

    Whereas the DELOS DRM and the 5S model of digital libraries (DL) addresses the formal side of DL, we argue that a parallel 5M model is emerging as best practice worldwide, integrating multicultural, multilingual, multimodal digital objects with multivariate statistics-based document indexing, categorization and retrieval methods. The fifth M stands for the modeling the information searching behavior of users, and of collection development. We show how an extension of the 5S model to Hilbert space (a) points toward the integration of several Ms; (b) makes the tracking of evolving semantic content feasible, and (c) leads to a field interpretation of word and sentence semantics underlying language change. First experimental results from the Strathprints e-repository verify the mathematical foundations of the 5M model.

  • 7.
    Darányi, Sándor
    et al.
    University of Borås, Faculty of Librarianship, Information, Education and IT.
    Wittek, Peter
    University of Borås, Faculty of Librarianship, Information, Education and IT.
    Conceptual machinery of the mythopoetic mind: Attis, a case study2015In: Proceedings of QI-15, 9th International Quantum Interaction Symposium, 2015Conference paper (Refereed)
    Abstract [en]

    In search for the right interpretation regarding a body of related content, we screened a small corpus of myths about Attis, a minor deity from the Hellenistic period in Asia Minor to identify the noncommutativity of key concepts used in storytelling. Looking at the protagonist's typical features, our experiment showed incompatibility with regard to his gender and downfall. A crosscheck for entanglement found no violation of a Bell inequality, its best approximation being on the border of the local polytope.

  • 8.
    Darányi, Sándor
    et al.
    University of Borås, Swedish School of Library and Information Science.
    Wittek, Peter
    University of Borås, Swedish School of Library and Information Science.
    Connecting the Dots: Mass, Energy, Word Meaning, and Particle-Wave Duality2012Conference paper (Refereed)
    Abstract [en]

    With insight from linguistics that degrees of text cohesion are similar to forces in physics, and the frequent use of the energy concept in text categorization by machine learning, we consider the applicability of particle-wave duality to semantic content inherent in index terms. Wave-like interpretations go back to the regional nature of such content, utilizing functions for its representation, whereas content as a particle can be conveniently modelled by position vectors. Interestingly, wave packets behave like particles, lending credibility to the duality hypothesis. We show in a classical mechanics framework how metaphorical term mass can be computed.

  • 9.
    Darányi, Sándor
    et al.
    University of Borås, Swedish School of Library and Information Science.
    Wittek, Peter
    University of Borås, Swedish School of Library and Information Science.
    Demonstrating Conceptual Dynamics in an Evolving Text Collection2013In: Journal of the Association for Information Science and Technology, ISSN 2330-1635, E-ISSN 2330-1643, Vol. 64, no 12, p. 2564-2572Article in journal (Refereed)
    Abstract [en]

    Based on real world user demands, we demonstrate how animated visualisation of evolving text corpora displays the underlying dynamics of semantic content. To interpret the results, one needs a dynamic theory of word meaning. We suggest that conceptual dynamics as the interaction between kinds of intellectual, emotional etc. content, and language, is key for such a theory. We demonstrate our methodology by two-way seriation which is a popular technique to analyse groups of similar instances and their features, as well as the connections between the groups themselves. The two-way seriated data may be visualised as a two-dimensional heat map or as a three-dimensional landscape where colour codes or height correspond to the values in the matrix. In this paper we focus on two-way seriation of sparse data in the Reuters-21568 test collection. To achieve a meaningful visualisation thereof we introduce a compactly supported convolution kernel similar to filter kernels used in image reconstruction and geostatistics. This filter populates the high-dimensional sparse space with values that interpolate nearby elements, and provides insight into the clustering structure. We also extend two-way seriation to deal with online updates of both the row and column spaces, and, combined with the convolution kernel, demonstrate a three-dimensional visualisation of dynamics.

  • 10.
    Darányi, Sándor
    et al.
    University of Borås, Swedish School of Library and Information Science.
    Wittek, Peter
    University of Borås, Swedish School of Library and Information Science.
    On Information, Meaning, Space and Geometry2009In: Exploration of Space, Technology and Spatiality: Interdisciplinary Perspectives / [ed] Susan Turner, E. D. P. Turner, Hersey: Idea Group , 2009Chapter in book (Other academic)
    Abstract [en]

    We offer a few general considerations, with theoretical overtones, working toward the definition and generation of a geometric language for practical purposes, prominently for information retrieval. This chapter is a non-mathematical introduction to the mathematical modelling of meaning of both words and sentences, outlining already existing components of such an endeavour, and hinting at directions of synthesis.

  • 11.
    Darányi, Sándor
    et al.
    University of Borås, Swedish School of Library and Information Science.
    Wittek, Peter
    University of Borås, Swedish School of Library and Information Science.
    The gravity of meaning: Physics as a metaphor to model semantic changes2012Conference paper (Refereed)
    Abstract [en]

    Based on a computed toy example, we offer evidence that by plugging in similarity of word meaning as a force plus a small modification of Newton’s 2nd law, one can acquire specific “mass” values for index terms in a Saltonesque dynamic library environment. The model can describe two types of change which affect the semantic composition of document collections: the expansion of a corpus due to its update, and fluctuations of the gravitational potential energy field generated by normative language use as an attractor juxtaposed with actual language use yielding time-dependent term frequencies. By the evolving semantic potential of a vocabulary and concatenating the respective term “mass” values, one can model sentences or longer strings of symbols as vector-valued functions. Since the line integral of such functions is used to express the work of a particle in a gravitational field, the work equivalent of strings can be calculated.

  • 12.
    Darányi, Sándor
    et al.
    University of Borås, Swedish School of Library and Information Science.
    Wittek, Peter
    University of Borås, Swedish School of Library and Information Science.
    Dobreva, Milena
    Position paper: Adding a 5M layer to the 5S model of digital libraries.2010Conference paper (Refereed)
    Abstract [en]

    We expect radical changes in document ( rst and foremost text) representation for digital libraries (DL) leading to new applications for documents processing.

  • 13.
    Darányi, Sándor
    et al.
    University of Borås, Swedish School of Library and Information Science.
    Wittek, Peter
    University of Borås, Swedish School of Library and Information Science.
    Dobreva, Milena
    Using wavelet analysis for text categorization in digital libraries: a first experiment with Strathprints2011In: International Journal on Digital Libraries, ISSN 1432-5012, E-ISSN 1432-1300Article in journal (Refereed)
    Abstract [en]

    Digital libraries increasingly bene t from re- search on automated text categorization for improved access. Such research is typically carried out by using standard test collections. In this paper we present a pilot experiment of replacing such test collections by a set of 6000 objects from a real-world digital repos- itory, indexed by Library of Congress Subject Head- ings, and test support vector machines in a supervised learning setting for their ability to reproduce the exist- ing classi cation. To augment the standard approach, we introduce a combination of two novel elements: us- ing functions for document content representation in Hilbert space, and adding extra semantics from lexical resources to the representation. Results suggest that wavelet-based kernels slightly outperformed traditional kernels on classi cation reconstruction from abstracts and vice versa from full-text documents, the latter out- come due to word sense ambiguity. The practical imple- mentation of our methodological framework enhances the analysis and representation of speci c knowledge relevant to large-scale digital collections, in this case the thematic coverage of the collections. Representation of speci c knowledge about digital collections is one of the basic elements of the persistent archives and the less studied one (compared to representations of digital ob- jects and collections). Our research is an initial step in this direction developing further the methodological ap- proach and demonstrating that text categorisation can be applied to analyse the thematic coverage in digital repositories.

  • 14.
    Darányi, Sándor
    et al.
    University of Borås, Swedish School of Library and Information Science.
    Wittek, Peter
    University of Borås, Swedish School of Library and Information Science.
    Forró, László
    Toward Sequencing “Narrative DNA”: Tale Types, Motif Strings and Memetic Pathways2012Conference paper (Other academic)
    Abstract [en]

    The Aarne-Thompson-Uther Tale Type Catalog (ATU) is a bibliographic tool which uses metadata from tale content, called motifs, to define tale types as canonical motif sequences. The motifs themselves are listed in another bibliographic tool, the Aarne-Thompson Motif Index (AaTh). Tale types in ATU are defined in an abstracted fashion and can be processed like a corpus. We analyzed 219 types with 1202 motifs from the “Tales of magic” (types 300-749) segment to exemplify that motif sequences show signs of recombination in the storytelling process. Compared to chromosome mutations in genetics, we offer examples for insertion/deletion, duplication and, possibly, transposition, whereas the sample was not sufficient to find inverted motif strings as well. These initial findings encourage efforts to sequence motif strings like DNA in genetics, attempting to find for instance the longest common motif subsequences in tales. Expressing the network of motif connections by graphs suggests that tale plots as consolidated pathways of content help one memorize culturally engraved messages. We anticipate a connection between such networks and addington’s epigenetic landscape.

  • 15.
    Darányi, Sándor
    et al.
    University of Borås, Swedish School of Library and Information Science.
    Wittek, Peter
    University of Borås, Swedish School of Library and Information Science.
    Kitto, Kirsty
    The Sphynx's new riddle: How to relate the canonical formula of myth to quantum interaction2013Conference paper (Refereed)
    Abstract [en]

    We introduce Claude Lévi Strauss' canonical formula (CF), an attempt to rigorously formalise the general narrative structure of myth. This formula utilises the Klein group as its basis, but a recent work draws attention to its natural quaternion form, which opens up the possibility that it may require a quantum inspired interpretation. We present the CF in a form that can be understood by a non-anthropological audience, using the formalisation of a key myth (that of Adonis) to draw attention to its mathematical structure. The future potential formalisation of mythological structure within a quantum inspired framework is proposed and discussed, with a probabilistic interpretation further generalising the formula.

  • 16.
    Darányi, Sándor
    et al.
    University of Borås, Faculty of Librarianship, Information, Education and IT.
    Wittek, Peter
    University of Borås, Faculty of Librarianship, Information, Education and IT.
    Konstantinidis, K
    CERTH..
    Papadopoulos, S
    CERTH..
    A Potential Surface Underlying Meaning?2015Conference paper (Other academic)
    Abstract [en]

    Machine learning algorithms utilizing gradient descent to identify concepts or more general learnables hint at a so-far ignored possibility, namely that local and global minima represent any vocabulary as a landscape against which evaluation of the results can take place. A simple example to illustrate this idea would be a potential surface underlying gravitation. However, to construct a gravitation-based representation of, e.g., word meaning, only the distance between localized items is a given in the vector space, whereas the equivalents of mass or charge are unknown in semantics. Clearly, the working hypothesis that physical fields could be a useful metaphor to study word and sentence meaning is an option but our current representations are incomplete in this respect.For a starter, consider that an RBF kernel has the capacity to generate a potential surface and hence create the impression of gravity, providing one with distance-based decay of interaction strength, plus a scalar scaling factor for the interaction, but of course no term masses. We are working on an experiment design to change that. Therefore, with certain mechanisms in neural networks that could host such quasi-physical fields, a novel approach to the modeling of mind content seems plausible, subject to scrutiny.Work in progress in another direction of the same idea indicates that by using certain algorithms, already emerged vs. still emerging content is clearly distinguishable, in line with Aristotle’s Metaphysics. The implications are that a model completed by “term mass” or “term charge” would enable the computation of the specific work equivalent of sentences or documents, and that via replacing semantics by other modalities, vector fields of more general symbolic content could exist as well. Also, the perceived hypersurface generated by the dynamics of language use may be a step toward more advanced models, for example addressing the Hamiltonian of expanding semantic systems, or the relationship between reaction paths in quantum chemistry vs. sentence construction by gradient descent.

  • 17.
    Darányi, Sándor
    et al.
    University of Borås, Faculty of Librarianship, Information, Education and IT.
    Wittek, Peter
    University of Borås, Faculty of Librarianship, Information, Education and IT.
    Konstantinidis, Konstantinos
    Papadopoulos, Symeon
    Kontopoulos, Efstratios
    A Physical Metaphor to Study Semantic Drift2016In: Proceedings of SuCCESS-16, 1st International Workshop on Semantic Change & Evolving Semantics, 2016, Vol. 1695Conference paper (Refereed)
    Abstract [en]

    In accessibility tests for digital preservation, over time we experience drifts of localized and labelled content in statistical models of evolving semantics represented as a vector field. This articulates the need to detect, measure, interpret and model outcomes of knowledge dynamics. To this end we employ a high-performance machine learning algorithm for the training of extremely large emergent self-organizing maps for exploratory data analysis. The working hypothesis we present here is that the dynamics of semantic drifts can be modeled on a relaxed version of Newtonian mechanics called social mechanics. By using term distances as a measure of semantic relatedness vs. their PageRank values indicating social importance and applied as variable ‘term mass’, gravitation as a metaphor to express changes in the semantic content of a vector field lends a new perspective for experimentation. From ‘term gravitation’ over time, one can compute its generating potential whose fluctuations manifest modifications in pairwise term similarity vs. social importance, thereby updating Osgood’s semantic differential. The dataset examined is the public catalog metadata of Tate Galleries, London.

  • 18.
    Gao, Shi Chao
    et al.
    Tsinghua University.
    Wittek, Peter
    University of Borås, Faculty of Librarianship, Information, Education and IT.
    Zhao, Li
    Jiang, Wen Jun
    Data-driven estimation of blood pressure using photoplethysmographic signals2016In: Proceedings of EMBC-16, 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2016Conference paper (Refereed)
    Abstract [en]

    Noninvasive measurement of blood pressure by optical methods receives considerable interest, but the complexity of the measurement and the difficulty of adjusting parameters restrict applications. We develop a method for estimating the systolic and diastolic blood pressure using a single-point optical recording of a photoplethysmographic (PPG) signal. The estimation is data-driven, we use automated machine learning algorithms instead of mathematical models. Combining supervised learning with a discrete wavelet transform, the method is insensitive to minor irregularities in the PPG waveform, hence both pulse oximeters and smartphone cameras can record the signal. We evaluate the accuracy of the estimation on 78 samples from 65 subjects (40 male, 25 female, age 29±7) with no history of cardiovascular disease. The estimate for systolic blood pressure has a mean error 4.9±4.9 mm Hg, and 4.3±3.7 mm Hg for diastolic blood pressure when using the oximeter-obtained PPG. The same values are 5.1±4.3 mm Hg and 4.6±4.3 mm Hg when using the phone-obtained PPG, comparing with A&D UA-767PBT result as gold standard. The simplicity of the method encourages ambulatory measurement, and given the ease of sharing the measured data, we expect a shift to data-oriented approaches deriving insight from ubiquitous mobile devices that will yield more accurate machine learning models in monitoring blood pressure.

  • 19. Jiang, Wen Jun
    et al.
    Gao, Shi Chao
    Wittek, Peter
    University of Borås, Swedish School of Library and Information Science.
    Zhao, Li
    Real-time Quantifying Heart Beat Rate from Facial Video Recording on a Smart Phone using Kalman Filters2014Conference paper (Refereed)
    Abstract [en]

    Photoplethysmography (PPG) can be carried out through facial video recording by a smart phone camera in ambient light. The main challenge is to eliminate motion artifacts and ambient noise. We describe a real-time algorithm to quantify the heart beat rate from facial video recording captured by the camera of a smart phone. We extract the green channel from the video. Then we normalize it and use a Kalman filter with a particular structure to eliminate ambient noise. This filter also enhances the heart pulse component in the signal distorted by Gaussian noise and white noise. After that we employ a band-pass FIR filter to remove the remaining motion artifacts. This is followed by peak detection or Lomb periodogram to estimate heart rate. The algorithm has low computational overhead, low delay and high robustness, making it suitable for real-time interaction on a smart phone. Finally we describe an Android application based on this study.

  • 20. Jiang, Wen jun
    et al.
    Wittek, Peter
    University of Borås, Swedish School of Library and Information Science.
    Zhao, Li
    Gao, Shi Chao
    Adaptive Thresholding with Inverted Triangular Area for Real-Time Detection of the Heart Rate from Photoplethysmogram Traces on a Smartphone2014Conference paper (Refereed)
    Abstract [en]

    Photoplethysmogram (PPG) signals acquired by smartphone cameras are weaker than those acquired by dedicated pulse oximeters. Furthermore, the signals have lower sampling rates, have notches in the waveform and are more severely affected by baseline drift, leading to specific morphological characteristics. This paper introduces a new feature, the inverted triangular area, to address these specific characteristics. The new feature enables real-time adaptive waveform detection using an algorithm of linear time complexity. It can also recognize notches in the waveform and it is inherently robust to baseline drift. An implementation of the algorithm on Android is available for free download. We collected data from 24 volunteers and compared our algorithm in peak detection with two competing algorithms designed for PPG signals, Incremental-Merge Segmentation (IMS) and Adaptive Thresholding (ADT). A sensitivity of 98.0 % and a positive predictive value of 98.8 % were obtained, which were 7.7 % higher than the IMS algorithm in sensitivity, and 8.3 % higher than the ADT algorithm in positive predictive value. The experimental results confirmed the applicability of the proposed method.

  • 21.
    Kontopoulos, E.
    et al.
    CERTH, Thessaloniki, Greece.
    Darányi, Sándor
    University of Borås, Faculty of Librarianship, Information, Education and IT.
    Wittek, Peter
    University of Borås, Faculty of Librarianship, Information, Education and IT.
    Konstantinidis, K.
    CERTH, Thessaloniki, Greece.
    Riga, M.
    CERTH, Thessaloniki, Greece.
    Mitzias, P.
    CERTH, Thessaloniki, Greece.
    Stavropoulos, T.
    CERTH, Thessaloniki, Greece.
    Andreadis, S.
    CERTH, Thessaloniki, Greece.
    Maronidis, A.
    CERTH, Thessaloniki, Greece.
    Karakostas, A.
    CERTH, Thessaloniki, Greece.
    Tachos, S.
    CERTH, Thessaloniki, Greece.
    Kaltsa, V.
    CERTH, Thessaloniki, Greece.
    Tsagiopoulu, M.
    CERTH, Thessaloniki, Greece.
    Avgerinakis, K.
    CERTH, Thessaloniki, Greece.
    Deliverable 4.5: Context-aware Content Interpretation2016Report (Refereed)
    Abstract [en]

    The current deliverable summarises the work conducted within task T4.5 of WP4, presenting our proposed approaches for contextualised content interpretation, aimed at gaining insightful contextualised views on content semantics. This is achieved through the adoption of appropriate context-aware semantic models developed within the project, and via enriching the semantic descriptions with background knowledge, deriving thus higher level contextualised content interpretations that are closer to human perception and appraisal needs. More specifically, the main contributions of the deliverable are the following: A theoretical framework using physics as a metaphor to develop different models of evolving semantic content. A set of proof-of-concept models for semantic drifts due to field dynamics, introducing two methods to identify quantum-like (QL) patterns in evolving information searching behaviour, and a QL model akin to particle-wave duality for semantic content classification. Integration of two specific tools, Somoclu for drift detection and Ncpol2spda for entanglement detection. An “energetic” hypothesis accounting for contextualized evolving semantic structures over time. A proposed semantic interpretation framework, integrating (a) an ontological inference scheme based on Description Logics (DL), (b) a rule-based reasoning layer built on SPARQL Inference Notation (SPIN), (c) an uncertainty management framework based on non-monotonic logics. A novel scheme for contextualized reasoning on semantic drift, based on LRM dependencies and OWL’s punning mechanism. An implementation of SPIN rules for policy and ecosystem change management, with the adoption of LRM preconditions and impacts. Specific use case scenarios demonstrate the context under development and the efficiency of the approach. Respective open-source implementations and experimental results that validate all the above.All these contributions are tightly interlinked with the other PERICLES work packages: WP2 supplies the use cases and sample datasets for validating our proposed approaches, WP3 provides the models (LRM and Digital Ecosystem models) that form the basis for our semantic representations of content and context, WP5 provides the practical application of the technologies developed to preservation processes, while the tools and algorithms presented in this deliverable can be deployed in combination with test scenarios, which will be part of the WP6 test beds.

  • 22. Kontopoulos, Efstratios
    et al.
    Moysiadis, Theodoros
    Tsagiopoulou, Maria
    Darányi, Sándor
    University of Borås, Faculty of Librarianship, Information, Education and IT.
    Wittek, Peter
    University of Borås, Faculty of Librarianship, Information, Education and IT.
    Papakonstantinou, Nikos
    Ntoufa, Stavroula
    Meditskos, Georgios
    Stamatopoulos, Kostas
    Kompatsiaris, Ioannis
    Studying the Cohesion Evolution of Genes Related to Chronic Lymphocytic Leukemia Using Semantic Similarity in Gene Ontology and Self-Organizing Maps2016In: Proceedings of SWAT4LS-16, 9th International Conference on Semantic Web Applications and Tools for Life Sciences, 2016Conference paper (Refereed)
    Abstract [en]

    A significant body of work on biomedical text mining is aimed at uncovering meaningful associations between biological entities, including genes. This has the potential to offer new insights for research, uncovering hidden links between genes involved in critical pathways and processes. Recently, high-throughput studies have started to unravel the genetic landscape of chronic lymphocytic leukemia (CLL), the most common adult leukemia. CLL displays remarkable clinical heterogeneity, likely reflecting its underlying biological heterogeneity which, despite all progress, still remains insufficiently characterized and understood. This paper deploys an ontology-based semantic similarity combined with self-organizing maps for studying the temporal evolution of cohesion among CLL-related genes and the extracted information. Three consecutive time periods are considered and groups of genes are derived therein. Our preliminary results indicated that our proposed gene groupings are meaningful and that the temporal dimension indeed impacted the gene cohesion, leaving a lot of room for further promising investigations.

  • 23.
    Kontopoulos, Efstratios
    et al.
    CERTH, Thessaloniki, Greece.
    Riga, Marina
    CERTH, Thessaloniki, Greece.
    Mitzias, P.
    CERTH, Thessaloniki, Greece.
    Andreadis, S.
    CERTH, Thessaloniki, Greece.
    Stavropoulos, T.
    CERTH, Thessaloniki, Greece.
    Konstantinidis, K.
    CERTH, Thessaloniki, Greece.
    Maronidis, A.
    CERTH, Thessaloniki, Greece.
    Karakostas, A.
    CERTH, Thessaloniki, Greece.
    Tachos, S.
    CERTH, Thessaloniki, Greece.
    Kaltsa, V.
    CERTH, Thessaloniki, Greece.
    Tsagiopoulu, M.
    CERTH, Thessaloniki, Greece.
    Darányi, Sándor
    University of Borås, Faculty of Librarianship, Information, Education and IT.
    Wittek, Peter
    University of Borås, Faculty of Librarianship, Information, Education and IT.
    Gill, A.
    King's College London, UK.
    Tonkin, E. L.
    King's College London, UK.
    Waddington, S.
    King's College London, UK.
    Sauter, Ch.
    King's College London, UK.
    Corubolo, F.
    University of Liverpool, UK.
    PERICLES Deliverable 4.4: Modelling Contextualised Semantics2016Report (Refereed)
    Abstract [en]

    The current deliverable summarises the work conducted within task T4.4 of WP4, presenting our proposed models for semantically representing digital content and its respective context – the latter refers to any information coming from the environment of the digital object (DO) that offers a better insight into the object’s status, its  interrelationships with other content items and information about the object’s context of use. Within PERICLES, we refer to the content semantics enriched with the contextual perspective as “contextualised semantics”. The deliverable presents two complementary modelling approaches, based respectively on (a) ontologies and logics, and, (b) multivariate statistics.

  • 24. Lim, Ik Soo
    et al.
    Wittek, Peter
    University of Borås, Faculty of Librarianship, Information, Education and IT.
    Parkinson, John
    On the Origin of Risk Sensitivity: The Energy Budget Rule Revisited2015In: Animal Behaviour, ISSN 0003-3472, E-ISSN 1095-8282, Vol. 110, p. 69-77Article in journal (Refereed)
    Abstract [en]

    The risk-sensitive foraging theory formulated in terms of the (daily) energy budget rule has been influential in behavioural ecology as well as other disciplines. Predicting risk-aversion on positive budgets and risk-proneness on negative budgets, however, the budget rule has recently been challenged both empirically and theoretically. In this paper, we critically review these challenges as well as the original derivation of the budget rule and propose a ‘gradual’ budget rule, which is normatively derived from a gradual nature of risk sensitivity and encompasses the conventional budget rule as a special case. The gradual budget rule shows that the conventional budget rule holds when the expected reserve is close enough to a threshold for overnight survival, selection pressure being significant. The gradual view also reveals that the conventional budget rule does not need to hold when the expected reserve is not close enough to the threshold, selection pressure being insignificant. The proposed gradual budget rule better fits the empirical findings including those that used to challenge the conventional budget rule.

  • 25.
    Maronidis, A.
    et al.
    CERTH, Thessaloniki, Greece.
    Chatzilari, E.
    CERTH, Thessaloniki, Greece.
    Kontopoulos, E.
    CERTH, Thessaloniki, Greece.
    Nikopoulos, S.
    CERTH, Thessaloniki, Greece.
    Riga, M.
    CERTH, Thessaloniki, Greece.
    Mitzias, P.
    CERTH, Thessaloniki, Greece.
    Darányi, Sándor
    University of Borås, Faculty of Librarianship, Information, Education and IT.
    Wittek, Peter
    University of Borås, Faculty of Librarianship, Information, Education and IT.
    Gill, A.
    King's College London, UK.
    Tonkin, E.L.
    King's College London, UK.
    De Weerdt, D.
    SpaceApps, Belgium.
    Corubolo, F.
    University of Liverpool, UK.
    Waddington, S.
    King's College London, UK.
    Sauter, Ch.
    King's College London, UK.
    PERICLES Deliverable 4.3: Content Semantics and Use Context Analysis Techniques2016Report (Refereed)
    Abstract [en]

    The current deliverable summarises the work conducted within task T4.3 of WP4, focusing on the extraction and the subsequent analysis of semantic information from digital content, which is imperative for its preservability. More specifically, the deliverable defines content semantic information from a visual and textual perspective, explains how this information can be exploited in long-term digital preservation and proposes novel approaches for extracting this information in a scalable manner. Additionally, the deliverable discusses novel techniques for retrieving and analysing the context of use of digital objects. Although this topic has not been extensively studied by existing literature, we believe use context is vital in augmenting the semantic information and maintaining the usability and preservability of the digital objects, as well as their ability to be accurately interpreted as initially intended.

  • 26. Meroño Peñuela, Albert
    et al.
    Wittek, Peter
    University of Borås, Faculty of Librarianship, Information, Education and IT.
    Darányi, Sándor
    University of Borås, Faculty of Librarianship, Information, Education and IT.
    Visualizing the Drift of Linked Open Data Using Self-Organizing Maps2016In: Proceedings of Drift-a-LOD Workshop at the 20th International Conference on Knowledge Engineering and Knowledge Management, 2016Conference paper (Refereed)
    Abstract [en]

    The urge for evolving the Web into a globally shared dataspace has turned the Linked Open Data (LOD) cloud into a massive platform containing 100 billion machine-readable statements. Several factors hamper a historical study of the evolution of the LOD cloud, and hence forecasting its future: its ever-growing scale, which makes a global analysis difficult; its Web-distributed nature, which challenges the analysis of its data; and the scarcity of regular and time-stamped archival dumps. Recently, a scalable implementation of self-organizing maps (SOM) has been developed to visualize the local topology of high-dimensional data. We use this methodology to address scalability issues, and the Dynamic Linked Data Observatory, a regular biweekly, centralized sample of the LOD cloud, as a time-stamped collection. We visualize the drift of Linked Datasets between 2012 and 2016, finding that datasets with high availability, high vocabulary reuse, and modeling with commonly used terms in the LOD cloud are better traceable across time.

  • 27. Monràs, Alex
    et al.
    Sentís, Gael
    Wittek, Peter
    University of Borås, Faculty of Librarianship, Information, Education and IT.
    Inductive quantum learning: Why you are doing it almost right2016In: arXiv, article id 1605.07541Article in journal (Refereed)
    Abstract [en]

    In supervised learning, an inductive learning algorithm extracts general rules from observed training instances, then the rules are applied to test instances. We show that this splitting of training and application arises naturally, in the classical setting, from a simple independence requirement with a physical interpretation of being non-signalling. Thus, two seemingly different definitions of inductive learning happen to coincide. This follows from very specific properties of classical information, which break down in the quantum setup. We prove a quantum de Finetti theorem for quantum channels, which shows that in the quantum case, the equivalence holds in the asymptotic setting (for large number of test instances). This reveals a natural analogy between classical learning protocols and their quantum counterparts, thus allowing to naturally enquire about standard elements in computational learning theory, such as structural risk minimization, model and sample complexity.

  • 28. Najim, Safa A.
    et al.
    Lim, Ik Soo
    Wittek, Peter
    University of Borås, Faculty of Librarianship, Information, Education and IT.
    Jones, Mark
    FSPE: Visualisation of Hyperspectral Imagery Using Faithful Stochastic Proximity Embedding2015In: IEEE Geoscience and Remote Sensing Letters, ISSN 1545-598X, E-ISSN 1558-0571, Vol. 12, no 1, p. 18-22Article in journal (Refereed)
    Abstract [en]

    Hyperspectral image visualization reduces color bands to three, but prevailing linear methods fail to address data characteristics, and nonlinear embeddings are computationally demanding. Qualitative evaluation of an embedding is also lacking. We propose Faithful Stochastic Proximity Embedding (FSPE), a scalable, nonlinear dimensionality reduction method. FSPE considers the nonlinear characteristics of spectral signatures, yet it avoids the costly computation of geodesic distances that are often required by other nonlinear methods. Furthermore, we introduce a point-wise metric that measures the quality of hyperspectral image visualization at each pixel. FSPE outperforms the state-of-art methods by at least 12% on average, and up to 25% in the proposed qualitative measure. An implementation on Graphics Processing Units (GPUs) is two magnitudes faster than the baseline. Our method opens the path to high-fidelity, real-time analysis of hyperspectral images.

  • 29. Oszmaniec, Michał
    et al.
    Guerini, Leonardo
    Wittek, Peter
    University of Borås, Faculty of Librarianship, Information, Education and IT.
    Acín, Antonio
    Simulating positive-operator-valued measures with projective measurements2016In: arXiv, article id 1609.06139Article in journal (Refereed)
    Abstract [en]

    Standard projective measurements represent a subset of all possible measurements in quantum physics. In fact, non-projective measurements are relevant for many applications, e.g. for estimation problems or transformations among entangled states. In this work we study what quantum measurements can be simulated by using only projective measurements and classical randomness. We first prove that every measurement on a given quantum system can be realised by a projective-simulable measurement on a system enlarged by an ancilla of the same dimension. Then, given a general measurement in dimension two or three, we show that deciding whether it is projective-simulable can be solved by means of semi-definite programming. We also establish conditions for the simulation of measurements using projective ones valid for any dimension. As an application of our formalism, we improve the range of visibilities for which two-qubit Werner states do not violate any Bell inequality for all measurements. From an implementation point of view, our results provide bounds on the amount of noise a general measurement tolerates before losing any advantage over projective ones.

  • 30. Palittapongarnpim, Pantita
    et al.
    Wittek, Peter
    University of Borås, Faculty of Librarianship, Information, Education and IT.
    Sanders, Barry C.
    Controlling adaptive quantum phase estimation with scalable reinforcement learning2016In: Proceedings of ESANN-16, 24th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, 2016, p. 327-332Conference paper (Refereed)
    Abstract [en]

    We develop a reinforcement-learning algorithm to construct a feedback policy that delivers quantum-enhanced interferometric-phase estimation up to 100 photons in a noisy environment. We ensure scalability of the calculations by distributing the workload in a cluster and by vectorizing time-critical operations. We also improve running time by introducing accept-reject criteria to terminate calculation when a successful result is reached. Furthermore, we make the learning algorithm robust to noise by fine-tuning how the objective function is evaluated. The results show the importance and relevance of well-designed classical machine learning algorithms in quantum physics problems.

  • 31. Palittapongarnpim, Pantita
    et al.
    Wittek, Peter
    University of Borås, Faculty of Librarianship, Information, Education and IT.
    Sanders, Barry C.
    Single-shot adaptive measurement for quantum-enhanced metrology2016In: Quantum Communications and Quantum Imaging XIV, 2016, Vol. 9980, article id 99800HConference paper (Refereed)
    Abstract [en]

    Quantum-enhanced metrology aims to estimate an unknown parameter such that the precision scales better than the shot-noise bound. Single-shot adaptive quantum-enhanced metrology (AQEM) is a promising approach that uses feedback to tweak the quantum process according to previous measurement outcomes. Techniques and formalism for the adaptive case are quite different from the usual non-adaptive quantum metrology approach due to the causal relationship between measurements and outcomes. We construct a formal framework for AQEM by modeling the procedure as a decision-making process, and we derive the imprecision and the Cram´er- Rao lower bound with explicit dependence on the feedback policy. We also explain the reinforcement learning approach for generating quantum control policies, which is adopted due to the optimal policy being non-trivial to devise. Applying a learning algorithm based on differential evolution enables us to attain imprecision for adaptive interferometric phase estimation, which turns out to be SQL when non-entangled particles are used in the scheme.

  • 32. Palittapongarnpim, Pantita
    et al.
    Wittek, Peter
    University of Borås, Faculty of Librarianship, Information, Education and IT.
    Zahedinejad, Ehsan
    Vedaie, Shakib
    Sanders, Barry C.
    Learning in Quantum Control: High-Dimensional Global Optimization for Noisy Quantum Dynamics2016In: arXiv, article id 1607.03428Article in journal (Refereed)
    Abstract [en]

    Quantum control is valuable for various quantum technologies such as high-fidelity gates for universal quantum computing, adaptive quantum-enhanced metrology, and ultra-cold atom manipulation. Although supervised machine learning and reinforcement learning are widely used for optimizing control parameters in classical systems, quantum control for parameter optimization is mainly pursued via gradient-based greedy algorithms. Although the quantum fitness landscape is often compatible for greedy algorithms, sometimes greedy algorithms yield poor results, especially for large-dimensional quantum systems. We employ differential evolution algorithms to circumvent the stagnation problem of non-convex optimization, and we average over the objective function to improve quantum control fidelity for noisy systems. To reduce computational cost, we introduce heuristics for early termination of runs and for adaptive selection of search subspaces. Our implementation is massively parallel and vectorized to reduce run time even further. We demonstrate our methods with two examples, namely quantum phase estimation and quantum gate design, for which we achieve superior fidelity and scalability than obtained using greedy algorithms.

  • 33. Salavrakos, Alexia
    et al.
    Augusiak, Remigiusz
    Tura, Jordi
    Wittek, Peter
    University of Borås, Faculty of Librarianship, Information, Education and IT.
    Acín, Antonio
    Pironio, Stefano
    Bell inequalities for maximally entangled states2016In: arXiv, article id 1607.04578Article in journal (Other academic)
    Abstract [en]

    Bell inequalities have traditionally been used to demonstrate that quantum theory is nonlocal, in the sense that there exist correlations generated from composite quantum states that cannot be explained by means of local hidden variables. With the advent of device-independent quantum information processing, Bell inequalities have gained an additional role as certificates of relevant quantum properties. In this work we consider the problem of designing Bell inequalities that are tailored to detect the presence of maximally entangled states. We introduce a class of Bell inequalities valid for an arbitrary number of measurements and results, derive analytically their maximal violation and prove that it is attained by maximally entangled states. Our inequalities can therefore find an application in device-independent protocols requiring maximally entangled states.

  • 34.
    Wittek, Peter
    University of Borås, Swedish School of Library and Information Science.
    High-Performance Dynamic Quantum Clustering on Graphics Processors2013In: Journal of Computational Physics, ISSN 0021-9991, E-ISSN 1090-2716, Vol. 233, p. 262-Article in journal (Refereed)
    Abstract [en]

    Clustering methods in machine learning may benefit from borrowing metaphors from physics. Dynamic quantum clustering associates a Gaussian wave packet with the multidimensional data points and regards them as eigenfunctions of the Schrödinger equation. The clustering structure emerges by letting the system evolve and the visual nature of the algorithm has been shown to be useful in a range of applications. Furthermore, the method only uses matrix operations, which readily lend themselves to parallelization. In this paper, we develop an implementation on graphics hardware and investigate how this approach can accelerate the computations. We achieve a speedup of up to two magnitudes over a multicore CPU implementation, which proves that quantum-like methods and acceleration by graphics processing units have a great relevance to machine learning.

  • 35.
    Wittek, Peter
    University of Borås, Faculty of Librarianship, Information, Education and IT.
    Ncpol2sdpa – Sparse Semidefinite Programming Relaxations for Polynomial Optimization Problems of Noncommuting Variables2015In: ACM Transactions on Mathematical Software, ISSN 0098-3500, E-ISSN 1557-7295, Vol. 41, no 3Article in journal (Refereed)
    Abstract [en]

    A hierarchy of semidefinite programming (SDP) relaxations approximates the global optimum of polynomial optimization problems of noncommuting variables. Generating the relaxation, however, is a computationally demanding task, and only problems of commuting variables have efficient generators. We develop an implementation for problems of noncommuting problems that creates the relaxation to be solved by SDPA -- a high-performance solver that runs in a distributed environment. We further exploit the inherent sparsity of optimization problems in quantum physics to reduce the complexity of the resulting relaxations. Constrained problems with a relaxation of order two may contain up to a hundred variables. The implementation is available in Python. The tool helps solve problems such as finding the ground state energy or testing quantum correlations.

  • 36.
    Wittek, Peter
    University of Borås, Swedish School of Library and Information Science.
    Quantum Machine Learning: What Quantum Computing Means to Data Mining2014Book (Other academic)
    Abstract [en]

    Quantum Machine Learning bridges the gap between abstract developments in quantum computing and the applied research on machine learning. Paring down the complexity of the disciplines involved, it focuses on providing a synthesis that explains the most important machine learning algorithms in a quantum framework. Theoretical advances in quantum computing are hard to follow for computer scientists, and sometimes even for researchers involved in the field. The lack of a step-by-step guide hampers the broader understanding of this emergent interdisciplinary body of research. Quantum Machine Learning sets the scene for a deeper understanding of the subject for readers of different backgrounds. The author has carefully constructed a clear comparison of classical learning algorithms and their quantum counterparts, thus making differences in computational complexity and learning performance apparent. This book synthesizes of a broad array of research into a manageable and concise presentation, with practical examples and applications.

  • 37.
    Wittek, Peter
    University of Borås, Swedish School of Library and Information Science.
    Somoclu: An Efficient Distributed Library for Self-Organizing Maps2013In: arXiv, E-ISSN 2331-8422Article in journal (Refereed)
    Abstract [en]

    Somoclu is a C++ tool for training self-organizing maps on large data sets using a high-performance cluster. It builds on MPI for distributing the workload across the nodes of the cluster. It is also able to boost training by using CUDA if graphics processing units are available. A sparse kernel is included, which is useful for high-dimensional but sparse data, such as the vector spaces common in text mining workflows. The code is released under GNU GPLv3 licence.

  • 38.
    Wittek, Peter
    University of Borås, Swedish School of Library and Information Science.
    Transduction and Active Learning in the Quantum Learning of Unitary Transformations2014Conference paper (Other academic)
    Abstract [en]

    Quantum learning of a unitary transformation estimates a quantum channel in a process similar to quantum process tomography. The classical counterpart of this goal, finding an unknown function, is regression, although the methodology hardly resembles the outline of classical algorithms. To gain a better understanding what such a methodology means to learning theory, we anchor it to the familiar concepts of active learning and transduction. Learning the unitary transformation translates to optimally storing it in quantum memory, but the quantum learning procedure also requires an optimal, maximally entangled input state. We argue that this is akin to active learning. Two different retrieval strategies apply when we would like to use the learned unitary transformation: a coherent strategy, which stores the unitary in quantum memory, and an incoherent one, which measures the unitary and stores it in classical memory; the latter strategy is considered optimal. We further argue that the incoherent strategy is a blend of inductive and transductive learning, as the optimal input state depends on the number of target states on which the transformation should be applied, yet once it is learned, the transformation can be used an arbitrary number of times. On the other hand, the sub-optimal coherent strategy of storing and applying the unitary is a form of transduction with no inductive element.

  • 39.
    Wittek, Peter
    University of Borås, Swedish School of Library and Information Science.
    Two-way incremental seriation in the temporal domain with three-dimensional visualization: Making sense of evolving high-dimensional data sets2013In: Computational Statistics & Data Analysis, ISSN 0167-9473, E-ISSN 1872-7352, Vol. 66, p. 193-201Article in journal (Refereed)
    Abstract [en]

    Two-way seriation is a popular technique to analyse groups of similar instances and their features, as well as the connections between the groups themselves. The two-way seriated data may be visualized as a two-dimensional heat map or as a three-dimensional landscape where colour codes or height correspond to the values in the matrix. To achieve a meaningful visualization of high-dimensional data, a compactly supported convolution kernel is introduced, which is similar to filter kernels used in image reconstruction and geostatistics. This filter populates the high-dimensional space with values that interpolate nearby elements, and provides insight into the clustering structure. Ordinary two-way seriation is also extended to deal with updates of both the row and column spaces. Combined with the convolution kernel, a three-dimensional visualization of dynamics is demonstrated on two data sets, a news collection and a set of microarray measurements.

  • 40.
    Wittek, Peter
    et al.
    University of Borås, Faculty of Librarianship, Information, Education and IT.
    Calderaro, Luca
    Extended computational kernels in a massively parallel implementation of the Trotter–Suzuki approximation2015In: Computer Physics Communications, ISSN 0010-4655, E-ISSN 1879-2944, Vol. 197, p. 339-340Article in journal (Other academic)
    Abstract [en]

    We extended a parallel and distributed implementation of the Trotter-Suzuki algorithm for simulating quantum systems to study a wider range of physical problems and to make the library easier to use. The new release allows periodic boundary conditions, many-body simulations of non-interacting particles, arbitrary stationary potential functions, and imaginary time evolution to approximate the ground state energy. The new release is more resilient to the computational environment: a wider range of compiler chains and more platforms are supported. To ease development, we provide a more extensive command-line interface, an application programming interface, and wrappers from high-level languages.

  • 41.
    Wittek, Peter
    et al.
    University of Borås, Swedish School of Library and Information Science.
    Cucchietti, Fernando M.
    A Second-Order Distributed Trotter-Suzuki Solver with a Hybrid CPU-GPU Kernel2013In: Computer Physics Communications, ISSN 0010-4655, E-ISSN 1879-2944, Vol. 184, p. 1165-1171Article in journal (Refereed)
    Abstract [en]

    The Trotter-Suzuki approximation leads to an efficient algorithm for solving the time-dependent Schrödinger equation. Using existing highly optimized CPU and GPU kernels, we developed a distributed version of the algorithm that runs efficiently on a cluster. Our implementation also improves single node performance, and is able to use multiple GPUs within a node. The scaling is close to linear using the CPU kernels, whereas the efficiency of GPU kernels improve with larger matrices. We also introduce a hybrid kernel that simultaneously uses multicore CPUs and GPUs in a distributed system. This kernel is shown to be efficient when the matrix size would not fit in the GPU memory. Larger quantum systems scale especially well with a high number nodes. The code is available under an open source license.

  • 42.
    Wittek, Peter
    et al.
    University of Borås, Swedish School of Library and Information Science.
    Darányi, Sándor
    University of Borås, Swedish School of Library and Information Science.
    A GPU-Accelerated Algorithm for Self-Organizing Maps in a Distributed Environment.2012Conference paper (Refereed)
    Abstract [en]

    In this paper we introduce a MapReduce-based implementation of self-organizing maps that performs compute-bound operations on distributed GPUs. The kernels are optimized to ensure coalesced memory access and effective use of shared memory. We have performed extensive tests of our algorithms on a cluster of eight nodes with two NVidia Tesla M2050 attached to each, and we achieve a 10x speedup for self-organizing maps over a distributed CPU algorithm.

  • 43.
    Wittek, Peter
    et al.
    University of Borås, Swedish School of Library and Information Science.
    Darányi, Sándor
    University of Borås, Swedish School of Library and Information Science.
    Accelerating Text Mining Workloads in a MapReduce-based Distributed GPU Environment2013In: Journal of Parallel and Distributed Computing, ISSN 0743-7315, E-ISSN 1096-0848, Vol. 73, no 2, p. 198-206Article in journal (Refereed)
    Abstract [en]

    Scientific computations have been using GPU-enabled computers successfully, often relying on distributed nodes to overcome the limitations of device memory. Only a handful of text mining applications benefit from such infrastructure. Since the initial steps of text mining are typically data intensive, and the ease of deployment of algorithms is an important factor in developing advanced applications, we introduce a flexible, distributed, MapReduce-based text mining workflow that performs I/O-bound operations on CPUs with industry-standard tools and then runs compute-bound operations on GPUs which are optimized to ensure coalesced memory access and effective use of shared memory. We have performed extensive tests of our algorithms on a cluster of eight nodes with two NVidia Tesla M2050s attached to each, and we achieve considerable speedups for random projection and self-organizing maps.

  • 44.
    Wittek, Peter
    et al.
    University of Borås, Swedish School of Library and Information Science.
    Darányi, Sándor
    University of Borås, Swedish School of Library and Information Science.
    Digital Preservation in Grids and Clouds: A Middleware Approach2012In: Journal of Grid Computing, ISSN 1570-7873, E-ISSN 1572-9184, Vol. 10, no 1, p. 133-149Article in journal (Refereed)
    Abstract [en]

    Digital preservation is the persistent archiving of digital assets for future access and reuse, irrespective of the underlying platform and software solutions. Existing preservation systems have a strong focus on grids, but the advent of cloud technologies offers an attractive option. We describe a middleware system that enables a flexible choice between a grid and a cloud for ad-hoc computations that arise during the execution of a preservation workflow and also for archiving digital objects. The choice between different infrastructures remains open during the lifecycle of the archive, ensuring a smooth switch between different solutions to accommodate the changing requirements of the organization that needs its digital assets preserved. We also offer insights on the costs, running times, and organizational issues of cloud computing, proving that the cloud alternative is particularly attractive for smaller organizations without access to a grid or with limited IT infrastructure.

  • 45.
    Wittek, Peter
    et al.
    University of Borås, Swedish School of Library and Information Science.
    Darányi, Sándor
    University of Borås, Swedish School of Library and Information Science.
    Introducing Scalable Quantum Approaches in Language Representation2011Conference paper (Refereed)
    Abstract [en]

    High-performance computational resources and distributed systems are crucial for the success of real-world language technology applications. The novel paradigm of general-purpose computing on graphics processors (GPGPU) o ers a feasible and economical alternative: it has already become a common phenomenon in scienti c computation, with many algorithms adapted to the new paradigm. However, applications in language technology do not readily adapt to this approach. Recent advances show the applicability of quantum metaphors in language representation, and many algorithms in quantum mechanics have already been adapted to GPGPU computing. SQUALAR aims to match quantum algorithms with heterogeneous computing to develop new formalisms of information representation for natural language processing in quantum environments.

  • 46.
    Wittek, Peter
    et al.
    University of Borås, Swedish School of Library and Information Science.
    Darányi, Sándor
    University of Borås, Swedish School of Library and Information Science.
    Leveraging on High-Performance Computing and Cloud Technologies in Digital Libraries: A Case Study2011Conference paper (Refereed)
    Abstract [en]

    With the emergence of high-performance computing instances in the cloud, massive scale computations have become available to technically every organization. Digital libraries typically employ a data-intensive infrastructure, but given the resources, advanced services based on data and text mining could be developed. A fundamental issue is the ease of development and integration of such services. We demonstrate the feasibility by providing a case study on a visual machine learning algorithm with MapReduce running in the cloud in a small cluster.

  • 47.
    Wittek, Peter
    et al.
    University of Borås, Swedish School of Library and Information Science.
    Darányi, Sándor
    University of Borås, Swedish School of Library and Information Science.
    Representing word semantics for IR by continuous functions2007In: Studies in Theory of Information Retrieval. Proceedings of the ICTIR07 Conference, Budapest, 18-20 October 2007 / [ed] Sándor Dominich, Ferenc Kiss, Foundation for Information Society, Budapest , 2007, p. 149-155Conference paper (Refereed)
    Abstract [en]

    Information representation is an important but neglected aspect of building text information retrieval models. In order to be efficient, the mathematical objects of a formal model, like vectors, have to reasonably reproduce language-related phenomena such as word meaning inherent in index terms. On the other hand, the classical vector space model, when it comes to the representation of word meaning, is approximative only, whereas it exactly localizes term, query and document content. It can be shown that by replacing vectors by continuous functions, information retrieval in Hilbert space yields comparable or better results. This is because according to the non-classical or continuous vector space model, content cannot be exactly localized. At the same time, the model relies on a richer representation of word meaning than the VSM can offer.

  • 48.
    Wittek, Peter
    et al.
    University of Borås, Swedish School of Library and Information Science.
    Darányi, Sándor
    University of Borås, Swedish School of Library and Information Science.
    Spectral Composition of Semantic Spaces2011Conference paper (Refereed)
    Abstract [en]

    Spectral theory in mathematics is key to the success of as diverse application domains as quantum mechanics and latent semantic indexing, both relying on eigenvalue decomposition for the localization of their respective entities in observation space. This points at some implicit \energy" inherent in semantics and in need of quanti cation. We show how the structure of atomic emission spectra, and meaning in concept space, go back to the same compositional principle, plus propose a tentative solution for the computation of term, document and collection \energy" content.

  • 49.
    Wittek, Peter
    et al.
    University of Borås, Swedish School of Library and Information Science.
    Darányi, Sándor
    University of Borås, Swedish School of Library and Information Science.
    Dobreva, Milena
    Matching Evolving Hilbert Spaces and Language for Semantic Access to Digital Libraries2010In: The Role of Digital Libraries in a Time of Global Change. Proceedings of the 12th International Conference on Asia-Pacific Digital Libraries, ICADL 2010, Gold Coast, Australia, June 21-25, 2010. / [ed] Gobinda Chowdhury, Chris Koo, Jane Hunter, Springer , 2010, p. 262-263Conference paper (Other academic)
    Abstract [en]

    Extended by function (Hilbert) spaces, the 5S model of digital libraries (DL) [1] enables a physical interpretation of vectors and functions to keep track of the evolving semantics and usage context of the digital objects by support vector machines (SVM) for text categorization (TC). For this conceptual transition, three steps are necessary: (1) the application of the formal theory of DL to Lebesgue (function, L2) spaces; (2) considering semantic content as vectors in the physical sense (i.e. position and direction vectors) rather than as in linear algebra, thereby modelling word semantics as an evolving field underlying classifications of digital objects; (3) the replacement of vectors by functions in a new compact support basis function (CSBF) semantic kernel utilizing wavelets for TC by SVMs.

  • 50.
    Wittek, Peter
    et al.
    University of Borås, Faculty of Librarianship, Information, Education and IT.
    Darányi, Sándor
    University of Borås, Faculty of Librarianship, Information, Education and IT.
    Kontopoulos, E.
    CERTH.
    Moysiadis, T.
    CERTH.
    Kompatsiaris, I.
    CERTH.
    Monitoring Term Drift Based on SemanticConsistency in an Evolving Vector Field2015In: Proceedings of IJCNN-15, 2015Conference paper (Refereed)
    Abstract [en]

    Based on the Aristotelian concept of potentialityvs. actuality allowing for the study of energy and dynamics inlanguage, we propose a field approach to lexical analysis. Fallingback on the distributional hypothesis to statistically model wordmeaning, we used evolving fields as a metaphor to express timedependentchanges in a vector space model by a combinationof random indexing and evolving self-organizing maps (ESOM).To monitor semantic drifts within the observation period, anexperiment was carried out on the term space of a collection of12.8 million Amazon book reviews. For evaluation, the semanticconsistency of ESOM term clusters was compared with theirrespective neighbourhoods in WordNet, and contrasted withdistances among term vectors by random indexing. We found thatat 0.05 level of significance, the terms in the clusters showed a highlevel of semantic consistency. Tracking the drift of distributionalpatterns in the term space across time periods, we found thatconsistency decreased, but not at a statistically significant level.Our method is highly scalable, with interpretations in philosophy.

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