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Semantic Search: Reconciling Expressive Querying and Exploratory Search

  • Sébastien Ferré
  • Alice Hermann
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7031)

Abstract

Faceted search and querying are two well-known paradigms to search the Semantic Web. Querying languages, such as SPARQL, offer expressive means for searching RDF datasets, but they are difficult to use. Query assistants help users to write well-formed queries, but they do not prevent empty results. Faceted search supports exploratory search, i.e., guided navigation that returns rich feedbacks to users, and prevents them to fall in dead-ends (empty results). However, faceted search systems do not offer the same expressiveness as query languages. We introduce Query-based Faceted Search (QFS), the combination of an expressive query language and faceted search, to reconcile the two paradigms. In this paper, the LISQL query language generalizes existing semantic faceted search systems, and covers most features of SPARQL. A prototype, Sewelis (aka. Camelis 2), has been implemented, and a usability evaluation demonstrated that QFS retains the ease-of-use of faceted search, and enables users to build complex queries with little training.

Keywords

Query Language Graph Pattern Current Selection Exploratory Search Navigation Place 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Brooke, J.: SUS: A quick and dirty usability scale. In: Jordan, P., Thomas, B., Weerdmeester, B., McClelland, A. (eds.) Usability Evaluation in Industry, pp. 189–194. Taylor and Francis, London (1996)Google Scholar
  2. 2.
    Ferré, S.: Camelis: a logical information system to organize and browse a collection of documents. Int. J. General Systems 38(4) (2009)Google Scholar
  3. 3.
    Ferré, S., Hermann, A., Ducassé, M.: Semantic faceted search: Safe and expressive navigation in RDF graphs. Research report, IRISA (2011), http://hal.inria.fr/inria-00410959/PDF/PI-1964.pdf
  4. 4.
    Ferré, S., Ridoux, O.: A File System Based on Concept Analysis. In: Palamidessi, C., Moniz Pereira, L., Lloyd, J.W., Dahl, V., Furbach, U., Kerber, M., Lau, K.-K., Sagiv, Y., Stuckey, P.J. (eds.) CL 2000. LNCS (LNAI), vol. 1861, pp. 1033–1047. Springer, Heidelberg (2000)CrossRefGoogle Scholar
  5. 5.
    Hearst, M., Elliott, A., English, J., Sinha, R., Swearingen, K., Yee, K.P.: Finding the flow in web site search. Communications of the ACM 45(9), 42–49 (2002)CrossRefGoogle Scholar
  6. 6.
    Heim, P., Ertl, T., Ziegler, J.: Facet Graphs: Complex Semantic Querying Made Easy. In: Aroyo, L., Antoniou, G., Hyvönen, E., ten Teije, A., Stuckenschmidt, H., Cabral, L., Tudorache, T. (eds.) ESWC 2010. LNCS, vol. 6088, pp. 288–302. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  7. 7.
    Hildebrand, M., van Ossenbruggen, J., Hardman, L.: /facet: A Browser for Heterogeneous Semantic Web Repositories. In: Cruz, I., Decker, S., Allemang, D., Preist, C., Schwabe, D., Mika, P., Uschold, M., Aroyo, L.M. (eds.) ISWC 2006. LNCS, vol. 4273, pp. 272–285. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  8. 8.
    Kaufmann, E., Bernstein, A.: Evaluating the usability of natural language query languages and interfaces to semantic web knowledge bases. J. Web Semantics 8(4), 377–393 (2010)CrossRefGoogle Scholar
  9. 9.
    Lu, J., Ma, L., Zhang, L., Brunner, J., Wang, C., Pan, Y., Yu, Y.: SOR: A practical system for ontology storage, reasoning and search (demo). In: Int. Conf. Very Large Databases (VLDB), pp. 1402–1405. VLDB Endowment, ACM (2007)Google Scholar
  10. 10.
    Marchionini, G.: Exploratory search: from finding to understanding. Communications of the ACM 49(4), 41–46 (2006)CrossRefGoogle Scholar
  11. 11.
    Oren, E., Delbru, R., Decker, S.: Extending Faceted Navigation for RDF Data. In: Cruz, I., Decker, S., Allemang, D., Preist, C., Schwabe, D., Mika, P., Uschold, M., Aroyo, L.M. (eds.) ISWC 2006. LNCS, vol. 4273, pp. 559–572. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  12. 12.
    Sacco, G.M.: Dynamic taxonomies: A model for large information bases. IEEE Transactions Knowledge and Data Engineering 12(3), 468–479 (2000)CrossRefGoogle Scholar
  13. 13.
    Sacco, G.M., Tzitzikas, Y. (eds.): Dynamic taxonomies and faceted search. The information retrieval series. Springer, Heidelberg (2009)Google Scholar
  14. 14.
    Tran, T., Wang, H., Haase, P.: Hermes: Data web search on a pay-as-you-go integration infrastructure. Web Semantics: Science, Services and Agents on the World Wide Web 7, 189–203 (2009)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Sébastien Ferré
    • 1
  • Alice Hermann
    • 2
  1. 1.IRISA/Université de RennesRennesFrance
  2. 2.IRISA/INSA de RennesRennesFrance

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