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Finding the N Best Vertices in an Infinite Weighted Hypergraph
Umeå University, Faculty of Science and Technology, Department of Computing Science. (Foundations of Language Processing)
Umeå University, Faculty of Science and Technology, Department of Computing Science. (Foundations of Language Processing)ORCID iD: 0000-0001-7349-7693
Umeå University, Faculty of Science and Technology, Department of Computing Science. (Foundations of Language Processing)
2017 (English)In: Theoretical Computer Science, ISSN 0304-3975, E-ISSN 1879-2294, Vol. 682, p. 78p. 30-41Article in journal (Refereed) Published
Abstract [en]

We propose an algorithm for computing the N best vertices in a weighted acyclic hypergraph over a nice semiring. A semiring is nice if it is finitely-generated, idempotent, and has 1 as its minimal element. We then apply the algorithm to the problem of computing the N best trees with respect to a weighted tree automaton, and complement theoretical correctness and complexity arguments with experimental data. The algorithm has several practical applications in natural language processing, for example, to derive the N most likely parse trees with respect to a probabilistic context-free grammar. 

Place, publisher, year, edition, pages
Elsevier, 2017. Vol. 682, p. 78p. 30-41
Keywords [en]
Hypergraph, N-best problem, Idempotent semiring
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:umu:diva-132501DOI: 10.1016/j.tcs.2017.03.010ISI: 000405062100005OAI: oai:DiVA.org:umu-132501DiVA, id: diva2:1081961
Note

Special Issue: SI

Available from: 2017-03-15 Created: 2017-03-15 Last updated: 2018-11-29Bibliographically approved
In thesis
1. Towards semantic language processing
Open this publication in new window or tab >>Towards semantic language processing
2018 (English)Licentiate thesis, comprehensive summary (Other academic)
Alternative title[sv]
Mot semantisk språkbearbetning
Abstract [en]

The overall goal of the field of natural language processing is to facilitate the communication between humans and computers, and to help humans with natural language problems such as translation. In this thesis, we focus on semantic language processing. Modelling semantics – the meaning of natural language – requires both a structure to hold the semantic information and a device that can enforce rules on the structure to ensure well-formed semantics while not being too computationally heavy. The devices used in natural language processing are preferably weighted to allow for comparison of the alternative semantic interpretations outputted by a device.

The structure employed here is the abstract meaning representation (AMR). We show that AMRs representing well-formed semantics can be generated while leaving out AMRs that are not semantically well-formed. For this purpose, we use a type of graph grammar called contextual hyperedge replacement grammar (CHRG). Moreover, we argue that a more well-known subclass of CHRG – the hyperedge replacement grammar (HRG) – is not powerful enough for AMR generation. This is due to the limitation of HRG when it comes to handling co-references, which in its turn depends on the fact that HRGs only generate graphs of bounded treewidth.

Furthermore, we also address the N best problem, which is as follows: Given a weighted device, return the N best (here: smallest-weighted, or more intuitively, smallest-errored) structures. Our goal is to solve the N best problem for devices capable of expressing sophisticated forms of semantic representations such as CHRGs. Here, however, we merely take a first step consisting in developing methods for solving the N best problem for weighted tree automata and some types of weighted acyclic hypergraphs.

Place, publisher, year, edition, pages
Umeå: Department of Computing Science, Umeå University, 2018. p. 16
Series
Report / UMINF, ISSN 0348-0542 ; 18.12
Keywords
Weighted tree automata, abstract meaning representation, contextual hyperedge replacement grammar, hyperedge replacement grammar, semantic modelling, the N best problem
National Category
Computer Sciences
Research subject
Computer Science; computational linguistics
Identifiers
urn:nbn:se:umu:diva-153738 (URN)978-91-7601-964-1 (ISBN)
Presentation
2018-12-07, MC413, Umeå, 10:00 (English)
Opponent
Supervisors
Available from: 2018-11-29 Created: 2018-11-28 Last updated: 2018-11-29Bibliographically approved

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