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Ranking methods for entity-oriented semantic web search

Ranking methods for entity-oriented semantic web search
Ranking methods for entity-oriented semantic web search
This article provides a technical review of semantic search methods used to support text-based search over formal Semantic Web knowledge bases. Our focus is on ranking methods and auxiliary processes explored by existing semantic search systems, outlined within broad areas of classification. We present reflective examples from the literature in some detail, which should appeal to readers interested in a deeper perspective on the various methods and systems implemented in the outlined literature. The presentation covers graph exploration and propagation methods, adaptations of classic probabilistic retrieval models, and query-independent link analysis via flexible extensions to the PageRank algorithm. Future research directions are discussed, including development of more cohesive retrieval models to unlock further potentials and uses, data indexing schemes, integration with user interfaces, and building community consensus for more systematic evaluation and gradual development.
information retrieval, semantic networks, keyword searching
1091-1106
Koumenides, Christos
ad4c9da8-e451-4f9a-80e5-fe66c7c006d7
Shadbolt, Nigel
5c5acdf4-ad42-49b6-81fe-e9db58c2caf7
Koumenides, Christos
ad4c9da8-e451-4f9a-80e5-fe66c7c006d7
Shadbolt, Nigel
5c5acdf4-ad42-49b6-81fe-e9db58c2caf7

Koumenides, Christos and Shadbolt, Nigel (2014) Ranking methods for entity-oriented semantic web search. Journal of the Association for Information Science and Technology, 65 (6), 1091-1106. (doi:10.1002/asi.23018).

Record type: Article

Abstract

This article provides a technical review of semantic search methods used to support text-based search over formal Semantic Web knowledge bases. Our focus is on ranking methods and auxiliary processes explored by existing semantic search systems, outlined within broad areas of classification. We present reflective examples from the literature in some detail, which should appeal to readers interested in a deeper perspective on the various methods and systems implemented in the outlined literature. The presentation covers graph exploration and propagation methods, adaptations of classic probabilistic retrieval models, and query-independent link analysis via flexible extensions to the PageRank algorithm. Future research directions are discussed, including development of more cohesive retrieval models to unlock further potentials and uses, data indexing schemes, integration with user interfaces, and building community consensus for more systematic evaluation and gradual development.

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e-pub ahead of print date: 12 March 2014
Published date: June 2014
Keywords: information retrieval, semantic networks, keyword searching
Organisations: Web & Internet Science

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Local EPrints ID: 363791
URI: https://eprints.soton.ac.uk/id/eprint/363791
PURE UUID: 968d89bb-f78b-4072-bb89-cfca4ca1ddec

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Date deposited: 04 Apr 2014 09:11
Last modified: 06 Aug 2019 18:46

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