Categorize by: deductive aggregation of semantic web query results

  • Authors:

  • Claudia d'Amato;Nicola Fanizzi;Agnieszka Ławrynowicz

  • Affiliations:

  • Dipartimento di Informatica, Universita degli Studi di Bari, Italy;Dipartimento di Informatica, Universita degli Studi di Bari, Italy;Institute of Computing Science, Poznan University of Technology, Poland

  • Venue:
  • ESWC'10 Proceedings of the 7th international conference on The Semantic Web: research and Applications - Volume Part I
  • Year:
  • 2010

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Abstract

Query answering on a wide and heterogeneous environment such as the Web can return a large number of results that can be hardly manageable by users/agents. The adoption of grouping criteria of the results could be of great help. Up to date, most of the proposed methods for aggregating results on the (Semantic) Web are mainly grounded on syntactic approaches. However, they could not be of significant help, when the values instantiating a grouping criterion are all equal (thus creating a unique group) or are almost all different (thus creating one group for each answer). We propose a novel approach that is able to overcome such drawbacks: given a query in the form of a conjunctive query, grouping is grounded on the exploitation of the semantics of background ontologies during the aggregation of query results. Specifically, we propose a solution where answers are deductively grouped taking into account the subsumption hierarchy of the underlying knowledge base. In this way, the results can be shown and navigated similarly to a faceted search. An experimental evaluation of the proposed method is also reported.