Web searching with entity mining at query time

  • Authors:

  • Pavlos Fafalios;Ioannis Kitsos;Yannis Marketakis;Claudio Baldassarre;Michail Salampasis;Yannis Tzitzikas

  • Affiliations:

  • Institute of Computer Science, FORTH-ICS, and Computer Science Department, University of Crete, Greece;Institute of Computer Science, FORTH-ICS, and Computer Science Department, University of Crete, Greece;Institute of Computer Science, FORTH-ICS, and Computer Science Department, University of Crete, Greece;Food and Agriculture Organization of the United Nations, Italy;Institute of Software Technology, and Interactive Systems, Vienna Univ. of Technology, Austria;Institute of Computer Science, FORTH-ICS, and Computer Science Department, University of Crete, Greece

  • Venue:
  • IRFC'12 Proceedings of the 5th conference on Multidisciplinary Information Retrieval
  • Year:
  • 2012

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Abstract

In this paper we present a method to enrich the classical web searching with entity mining that is performed at query time. The results of entity mining (entities grouped in categories) can complement the query answers with useful for the user information which can be further exploited in a faceted search-like interaction scheme. We show that the application of entity mining over the snippets of the top-hits of the answers, can be performed at real-time. However mining over the snippets returns less entities than mining over the full contents of the hits, and for this reason we report comparative results for these two scenarios. In addition, we show how Linked Data can be exploited for specifying the entities of interest and for providing further information about the identified entities, implementing a kind of entity-based integration of documents and (semantic) data. Finally, we discuss the applicability of this approach on professional search, specifically for the domains of fisheries/aquaculture and patents.