ABSTRACT
Due to the increasing volume of and interconnections between semantic datasets, it becomes a challenging task for novice users to know what are included in a dataset, how they can make use of them, and particularly, what queries should be asked. In this paper we analyse several types of candidate insightful queries and propose a framework to generate such queries and identify their relations. To verify our approach, we implemented our framework and evaluated its performance with benchmark and real world datasets.
- F. Baader, M. Bienvenu, C. Lutz, F. Wolter, et al. Query and predicate emptiness in description logics. Proc. of KR2010.Google Scholar
- G. Chatzopoulou, M. Eirinaki, and N. Polyzotis. Query recommendations for interactive database exploration. In Proc. of SSDBM 2009, pages 3--18, 2009. Google ScholarDigital Library
- M. d'Aquin and E. Motta. Extracting Relevant Questions to an RDF Dataset Using Formal Concept Analysis. In Proceedings of the sixth international conference on Knowledge capture, pages 121--128, 2011. Google ScholarDigital Library
- A. Fokoue, F. Meneguzzi, M. Sensoy, and J. Z. Pan. Querying linked ontological data through distributed summarization. In AAAI2012.Google Scholar
- O. Görlitz, M. Thimm, and S. Staab. Splodge: Systematic generation of sparql benchmark queries for linked open data. In Proc. of ISWC 2012, pages 116--132. Springer, 2012. Google ScholarDigital Library
- B. C. Grau and G. Stoilos. What to Ask to an Incomplete Semantic Web Reasoner? In IJCAI, pages 2226--2231, 2011. Google ScholarDigital Library
- N. Heino and J. Z. Pan. RDFS Reasoning on Massively Parallel Hardware. In Proc. of ISWC2012. Google ScholarDigital Library
- J. Lehmann, S. Auer, L. Bühmann, and S. Tramp. Class expression learning for ontology engineering. Journal of Web Semantics, 9:71--81, 2011. Google ScholarDigital Library
- C. Mishra, N. Koudas, and C. Zuzarte. Generating Targeted Queries for Database Testing. In Proc. of SIGMOD, 2008. Google ScholarDigital Library
- J. Z. Pan, E. Thomas, Y. Ren, and S. Taylor. Tractable Fuzzy and Crisp Reasoning in Ontology Applications. In IEEE Computational Intelligence Magazine, 2012.Google ScholarDigital Library
- J. Quinlan and R. Cameron-Jones. Foil: A midterm report. In Machine Learning: ECML-93, pages 1--20. Springer, 1993. Google ScholarDigital Library
- W. Siberski, J. Z. Pan, and U. Thaden. Querying the semantic web with preferences. In Proc. of ISWC2006. Google ScholarDigital Library
- D. Slutz. Massive Stochastic Testing of SQL. In VLDB, pages 618--622, 1998. Google ScholarDigital Library
- J. Völker and M. Niepert. Statistical schema induction. The Semantic Web: Research and Applications, 2011. Google ScholarDigital Library
- Z. Zhang and O. Nasraoui. Mining search engine query logs for query recommendation. In Proc. of WWW2006. Google ScholarDigital Library
Index Terms
- Query generation for semantic datasets
Recommendations
RDF, Jena, SparQL and the 'Semantic Web'
SIGUCCS '09: Proceedings of the 37th annual ACM SIGUCCS fall conference: communication and collaborationThe Resource Description Format (RDF) is used to represent information modeled as a "graph": a set of individual objects, along with a set of connections among those objects. In that role, RDF is one of the pillars of the so-called Semantic Web. This ...
Using SPARQL to query bioportal ontologies and metadata
ISWC'12: Proceedings of the 11th international conference on The Semantic Web - Volume Part IIBioPortal is a repository of biomedical ontologies--the largest such repository, with more than 300 ontologies to date. This set includes ontologies that were developed in OWL, OBO and other languages, as well as a large number of medical terminologies ...
Comments