Document (#37232)

Author

Zhang, L.
Liu, Q.L.
Zhang, J.
Wang, H.F.
Pan, Y.
Yu, Y.

Title

Semplore: an IR approach to scalable hybrid query of Semantic Web data

Source

Proceeding ISWC'07/ASWC'07 : Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference. Ed.: K. Aberer et al

Imprint

Berlin : Springer

Year

2007

Pages

S.652-665

Series

Lecture notes in computer science; 4825

Abstract

As an extension to the current Web, Semantic Web will not only contain structured data with machine understandable semantics but also textual information. While structured queries can be used to find information more precisely on the Semantic Web, keyword searches are still needed to help exploit textual information. It thus becomes very important that we can combine precise structured queries with imprecise keyword searches to have a hybrid query capability. In addition, due to the huge volume of information on the Semantic Web, the hybrid query must be processed in a very scalable way. In this paper, we define such a hybrid query capability that combines unary tree-shaped structured queries with keyword searches. We show how existing information retrieval (IR) index structures and functions can be reused to index semantic web data and its textual information, and how the hybrid query is evaluated on the index structure using IR engines in an efficient and scalable manner. We implemented this IR approach in an engine called Semplore. Comprehensive experiments on its performance show that it is a promising approach. It leads us to believe that it may be possible to evolve current web search engines to query and search the Semantic Web. Finally, we briefy describe how Semplore is used for searching Wikipedia and an IBM customer's product information.

Content

Vgl.: http://mathcs.emory.edu/~qliu26/docs/iswc07.pdf.

Theme

Semantic Web
Wissensrepräsentation

Object

Semplore

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3. Starostenko, O.; Rodríguez-Asomoza, J.; Sénchez-López, S.E.; Chévez-Aragón, J.A.: Shape indexing and retrieval : a hybrid approach using ontological description (2008) 0.34

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4. Layfield, C.; Azzopardi, J,; Staff, C.: Experiments with document retrieval from small text collections using Latent Semantic Analysis or term similarity with query coordination and automatic relevance feedback (2017) 0.23

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5. Cortez, E.M.; Park, S.C.; Kim, S.: ¬The hybrid application of an inductive learning method and a neural network (1995) 0.23

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