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Introducing Diversity to Log-Based Query Suggestions to Deal with Underspecified User Queries

  • Marcin Sydow
  • Krzysztof Ciesielski
  • Jakub Wajda
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7053)

Abstract

This paper presents novel approaches to deal with ambiguous or under-specified user queries in search engines. We propose two algorithms for automatic query suggestion that are based on query logs. Furthermore, we propose a novel approach of diversifying the suggestions in order to improve user experience and present a novel adaptation of the MMR diversification algorithm to this problem. We propose two novel query-similarity measures that are utilised by the algorithm. We also present promising preliminary experimental results that are conducted on real data.

Keywords

Semantic Similarity User Query Preliminary Experimental Result Semantic Similarity Measure Query Suggestion 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Marcin Sydow
    • 1
    • 2
  • Krzysztof Ciesielski
    • 1
  • Jakub Wajda
    • 1
  1. 1.Institute of Computer SciencePolish Academy of SciencesWarsawPoland
  2. 2.Polish-Japanese Institute of Information TechnologyWarsawPoland

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