Squirrel: An Advanced Semantic Search and Browse Facility

Search is seen as a key application that can benefit from semantic technology with improvements to recall and precision over conventional Information Retrieval techniques. This paper describes Squirrel, a search and browse tool that provides access to semantically annotated data. Squirrel provides combined keyword based and semantic searching. The intention is to provide a balance between the speed and ease of use of simple free text search and the power of semantic search. In addition, the ontological approach provides the user with a much richer browsing experience. Squirrel builds on and integrates a number of semantic technology components. These include machine learning and information extraction components which generate, extract and manage semantic metadata contained within and about textual documents at index time. A number of run-time components have also been integrated to deliver an enhanced user experience which goes beyond merely presenting a list of documents as a query response. The tool has been trialled and evaluated in two case studies and we report early results from this exercise, revealing promising results.

[1]  Atanas Kiryakov,et al.  OWLIM - A Pragmatic Semantic Repository for OWL , 2005, WISE Workshops.

[2]  Wei-Ying Ma,et al.  Implicit link analysis for small web search , 2003, SIGIR '03.

[3]  Dunja Mladenic,et al.  Semantics, Web and Mining , 2008 .

[4]  Dean Allemang,et al.  The Semantic Web - ISWC 2006, 5th International Semantic Web Conference, ISWC 2006, Athens, GA, USA, November 5-9, 2006, Proceedings , 2006, SEMWEB.

[5]  Robert Dale,et al.  Building Natural Language Generation Systems: Figures , 2000 .

[6]  T. Glover,et al.  Integrating device independence and user profiles on the Web , 2005 .

[7]  Atanas Kiryakov,et al.  KIM – a semantic platform for information extraction and retrieval , 2004, Natural Language Engineering.

[8]  Boris Motik,et al.  Reducing SHIQ-Description Logic to Disjunctive Datalog Programs , 2004, KR.

[9]  Brian P. Kettler,et al.  The Concept Object Web for Knowledge Management , 2005, SEMWEB.

[10]  Lynda Hardman,et al.  /facet: A Browser for Heterogeneous Semantic Web Repositories , 2006, SEMWEB.

[11]  Kalina Bontcheva Generating Tailored Textual Summaries from Ontologies , 2005, ESWC.

[12]  Scott P. Robertson,et al.  Proceedings of the SIGCHI Conference on Human Factors in Computing Systems , 1991 .

[13]  Enrico Motta,et al.  The Semantic Web - ISWC 2005, 4th International Semantic Web Conference, ISWC 2005, Galway, Ireland, November 6-10, 2005, Proceedings , 2005, SEMWEB.

[14]  Robin Jeffries,et al.  Applying cognitive walkthroughs to more complex user interfaces: experiences, issues, and recommendations , 1992, CHI.

[15]  Quan Z. Sheng,et al.  Web Information Systems Engineering - Wise 2005 Workshops , 2008 .

[16]  Ehud Reiter,et al.  Book Reviews: Building Natural Language Generation Systems , 2000, CL.

[17]  Freddy Y. Y. Choi Advances in domain independent linear text segmentation , 2000, ANLP.

[18]  Amanda Spink,et al.  Real life, real users, and real needs: a study and analysis of user queries on the web , 2000, Inf. Process. Manag..

[19]  Najafi Azadeh,et al.  REAL LIFE, REAL USERS AND REAL NEEDS: A STUDY AND ANALYSIS OF USER QUERIES ON THE WEB , 2008 .

[20]  Dunja Mladenic,et al.  Semi-automatic Construction of Topic Ontologies , 2005, EWMF/KDO.

[21]  D. Mladení,et al.  Semi-automatic construction of topic ontology , 2005 .

[22]  Jakob Nielsen,et al.  Heuristic evaluation of user interfaces , 1990, CHI '90.