SWHi System Description: A Case Study in Information Retrieval, Inference, and Visualization in the Semantic Web

Authors:
Ismail Fahmi;Junte Zhang;Henk Ellermann;Gosse Bouma
Affiliations:
Information Science Department and University Library, University of Groningen, Broerstraat 4, 9712 CP Groningen, The Netherlands;Information Science Department and University Library, University of Groningen, Broerstraat 4, 9712 CP Groningen, The Netherlands;Information Science Department and University Library, University of Groningen, Broerstraat 4, 9712 CP Groningen, The Netherlands;Information Science Department and University Library, University of Groningen, Broerstraat 4, 9712 CP Groningen, The Netherlands
Venue:
ESWC '07 Proceedings of the 4th European conference on The Semantic Web: Research and Applications
Year:
2007

Citing 7
Cited 0

Graph drawing by force-directed placement

Software—Practice & Experience
The Eyes Have It: A Task by Data Type Taxonomy for Information Visualizations

VL '96 Proceedings of the 1996 IEEE Symposium on Visual Languages
Visualization of Semantic Metadata and Ontologies

IV '03 Proceedings of the Seventh International Conference on Information Visualization
QuizRDF: Search Technology for the Semantic Web

HICSS '04 Proceedings of the Proceedings of the 37th Annual Hawaii International Conference on System Sciences (HICSS'04) - Track 4 - Volume 4
How to make a semantic web browser

Proceedings of the 13th international conference on World Wide Web
Information Retrieval and the Semantic Web

HICSS '05 Proceedings of the Proceedings of the 38th Annual Hawaii International Conference on System Sciences (HICSS'05) - Track 4 - Volume 04
Semantic annotation, indexing, and retrieval

Web Semantics: Science, Services and Agents on the World Wide Web

Quantified Score

Hi-index	0.00

Visualization

Abstract

Search engines have become the most popular tools for finding information on the Internet. A real-world Semantic Web application can benefit from this by combining its features with some features from search engines. In this paper, we describe methods for indexing and searching a populated ontology by using an information retrieval tool; its results are enriched with inference. For visualization purposes, all of the retrieved ontology instances are clustered based on their classes; and the clusters are linked using instance properties. The approach is illustrated using our SWHi (Semantic Web for History) prototype as a case study.