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A Domain Specific Search Engine WithExplicit Document Relations
KTH, School of Information and Communication Technology (ICT).
2013 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

The current web consists of documents that are highly heterogeneous and hard for machines to understand. The SemanticWeb is a progressive movement of the Word Wide Web, aiming at converting the current web of unstructured documents to the web of data. In the Semantic Web, web documents are annotated with metadata using standardized ontology language. These annotated documents are directly processable by machines and it highly improves their usability and usefulness. In Ericsson, similar problems occur. There are massive documents being created with well-defined structures. Though these documents are about domain specific knowledge and can have rich relations, they are currently managed by a traditional search engine, which ignores the rich domain specific information and presents few data to users. Motivated by the Semantic Web, we aim to find standard ways to process these documents, extract rich domain specific information and annotate these data to documents with formal markup languages. We propose this project to develop a domain specific search engine for processing different documents and building explicit relations for them. This research project consists of the three main focuses: examining different domain specific documents and finding ways to extract their metadata; integrating a text search engine with an ontology server; exploring novel ways to build relations for documents. We implement this system and demonstrate its functions. As a prototype, the system provides required features and will be extended in the future.

Place, publisher, year, edition, pages
2013. , 55 p.
TRITA-ICT-EX, 2013:184
National Category
Computer and Information Science
URN: urn:nbn:se:kth:diva-141654OAI: diva2:697394
Educational program
Master of Science - Distributed Computing
Available from: 2014-02-20 Created: 2014-02-18 Last updated: 2014-02-20Bibliographically approved

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