Advancing Search Query Autocompletion Services with More and Better Suggestions

  • Dimitrios Kastrinakis
  • Yannis Tzitzikas
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6189)


Autocompletion services help users in formulating queries by exploiting past queries. In this paper we propose methods for improving such services; specifically methods for increasing the number and the quality of the suggested “completions”. In particular, we propose a novel method for partitioning the internal data structure that keeps the suggestions, making autocompletion services more scalable and faster. In addition we introduce a ranking method which promotes a suggestion that can lead to many other suggestions. The experimental and empirical results are promising.


Main Memory Ranking Method Internal Data Structure Ranking Formula News Group 
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 2010

Authors and Affiliations

  • Dimitrios Kastrinakis
    • 1
  • Yannis Tzitzikas
    • 1
    • 2
  1. 1.Computer Science DepartmentUniversity of CreteGreece
  2. 2.Institute of Computer ScienceFORTH-ICSGreece

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