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Ranking of Resulting Objects and Snippet Generation for Falcons

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IP Multimedia Communications
© 2011 by IJCA Journal
ISBN : 978-93-80864-99-3
Year of Publication: 2011
Authors:
Pokhar M Jat
Manoj K Jain
Deepak Sengar

Pokhar M Jat, Manoj K Jain and Deepak Sengar. Ranking of Resulting Objects and Snippet Generation for Falcons. Special issues on IP Multimedia Communications (1):151-154, October 2011. Full text available. BibTeX

@article{key:article,
	author = {Pokhar M Jat and Manoj K Jain and Deepak Sengar},
	title = {Ranking of Resulting Objects and Snippet Generation for Falcons},
	journal = {Special issues on IP Multimedia Communications},
	month = {October},
	year = {2011},
	number = {1},
	pages = {151-154},
	note = {Full text available}
}

Abstract

Semantic web search engine Falcons support keyword based search for linked objects by using comprehensive virtual document which it creates for each object. In our work we are suggesting idea of using Selectivity Estimation of triple patterns for ranking of resulting objects and generating snippet for the keyword query for Falcons Semantic web search engine. Selectivity of a triple pattern is the fraction of triple satisfying the keyword query. Our work ranks resulting objects considering their relevance to the keyword query. For each resulting object for a searched keyword query, Object-rank is calculated by calculating the query-relevant-index for each RDF triple related to the object. For each resulting object, a query relevant structured snippet is provided to show the associated literals and linked objects matched with the query. Snippet generation is also done by query-relevant index of RDF triples related to the resulting object.

Reference

  1. Cheng Gong & Qu Yuzhong, Searching Linked Objects with Falcons: Approach, Implementation and Evaluation. In International Journal on Semantic Web and Information System, 5(3), 50-71, July-September 2009
  2. X. Zhang, G. Chang & Y. Qu (2007). Ontology Summarization based on RDF Sentence Graph. In C. Williamson, M. E. Zurko, P. Patel-Schneider, & P.Shenoy (Eds.), Proceedings of the 16th International Conference on World Wide Web (pp. 707-716). New York,NY,USA: ACM
  3. G. Tummarello, C. Morbidoini, R. Bachmann-Gmur, & O. Erling (2007). RDF Sync: Efficient Remote Synchronization of RDF Models. In K. Aberer et al. (Eds.), Proceedings of the 6th Semantic web Conference and the 2nd Asian Semantic web Conference (Vol. 4825, pp. 537 - 551). Berlin/Heidelberg: Springer.
  4. T. Tran, P. Cimiano, S.Rudolph, & R. Studer (2007). Ontologu Based Interpretation of Keywords for Semantic Search. In K. Aberer et al. (Eds), Proceedings of the 6th Semantic web Conference and the 2nd Asian Semantic web Conference (Vol. 4825, pp. 523 - 536). Berlin/Heidelberg: Springer.
  5. A. Bernstein, C. Kiefer, and M. Stocker. OptARQ: A SPARQL Optimization Approach based on Triple Pattern Selectivity Estimation(Section 2). Technical Report IFI-2007.02, Department of Informatics, University of Zurich, 2007..
  6. M. Arenas, M. Consens, and A. Mallea. Revisiting Blank Nodes in RDF to Avoid the Semantic Mismatch with SPARQL. (Section 2)
  7. G. Antoniou, and F. van Harmelen. Semantic web Primer, 2nd edition. Chapter 3 & 4.
  8. C. Waters (1999). Information Retrieval and Virtual Document. Journal of the American Society for Information Science, 50(11), 1028-1029.
  9. W3C, Resource Description Framework(RDF): Concepts and Abstract Syntax, Section 6.6 Blank Nodes.
  10. Y. Qu, W. Hu, & G. Chang (2006). Constructing Virtual Documents for Ontology Matching. In L. Carr, D. D. Roure, A. Iyengar, C. Goble, & M.Dahlin (Eds.), Proceedings of the 15th International Conference on World Wide Web (pp. 23-31). New York, NY, USA:ACM.
  11. Q. Zhou, C. Wang, M. Xiong, H. Wang, & Y. Yu (2007). SPARK: adapting keyword query to semantic search. In K. Aberer et al. (Eds.), Proceedings of 6th International Semantic Web Conference and the 2nd Asian Semantic Web Conference (Vol. 4825, pp. 694-707), Berlin/Heidelberg: Springer.
  12. H. Wang, K. Zhang, Q. Liu., T. Tran, & Y. Yu. (2008). Q2Semantic: a Lightweight Keyword Based Interface to Semantic Search. In S. Bechhofer, M. Hausewirth, J. Hauffmann, & M. Koubarakis (Eds.), Proceedings of 5th European Semantic Web Conference (Vol. 5021, pp. 584-598). Berlin/Heidelberg: Springer