Search (7 results, page 1 of 1)

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Abstract

In this thesis, we present an ontology-based information extraction and retrieval system and its application to soccer domain. In general, we deal with three issues in semantic search, namely, usability, scalability and retrieval performance. We propose a keyword-based semantic retrieval approach. The performance of the system is improved considerably using domain-specific information extraction, inference and rules. Scalability is achieved by adapting a semantic indexing approach. The system is implemented using the state-of-the-art technologies in SemanticWeb and its performance is evaluated against traditional systems as well as the query expansion methods. Furthermore, a detailed evaluation is provided to observe the performance gain due to domain-specific information extraction and inference. Finally, we show how we use semantic indexing to solve simple structural ambiguities.

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Abstract

Robertson and Spärck Jones pioneered experimental probabilistic models (Binary Independence Model) with both a typology generalizing the Boolean model, a frequency counting to calculate elementary weightings, and their combination into a global probabilistic estimation. However, this model did not consider indexing terms dependencies. An extension to mixture models (e.g., using a 2-Poisson law) made it possible to take into account these dependencies from a macroscopic point of view (BM25), as well as a shallow linguistic processing of co-references. New approaches (language models, for example "bag of words" models, probabilistic dependencies between requests and documents, and consequently Bayesian inference using Dirichlet prior conjugate) furnished new solutions for documents structuring (categorization) and for index smoothing. Presently, in these probabilistic models the main issues have been addressed from a formal point of view only. Thus, linguistic properties are neglected in the indexing language. The authors examine how a linguistic and semantic modeling can be integrated in indexing languages and set up a hybrid model that makes it possible to deal with different information retrieval problems in a unified way.

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Date

26.12.2011 13:40:22

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Source

Bulletin of the Association for Information Science and Technology. 41(2015) no.4, S.18-22

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Abstract

The main purpose of this book is to sum up the vital and highly topical research issue of knowledge representation on the Web and to discuss novel solutions by combining benefits of folksonomies and Web 2.0 approaches with ontologies and semantic technologies. This book contains an overview of knowledge representation approaches in past, present and future, introduction to ontologies, Web indexing and in first case the novel approaches of developing ontologies. This title combines aspects of knowledge representation for both the Semantic Web (ontologies) and the Web 2.0 (folksonomies). Currently there is no monographic book which provides a combined overview over these topics. focus on the topic of using knowledge representation methods for document indexing purposes. For this purpose, considerations from classical librarian interests in knowledge representation (thesauri, classification schemes etc.) are included, which are not part of most other books which have a stronger background in computer science.

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Date

16.11.2018 14:22:01

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Date

20. 1.2015 18:30:22