Exploring Ant Colony Optimisation for Adaptive Interactive Search

  • M-Dyaa Albakour
  • Udo Kruschwitz
  • Nikolaos Nanas
  • Dawei Song
  • Maria Fasli
  • Anne De Roeck
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6931)

Abstract

Search engines have become much more interactive in recent years which has triggered a lot of work in automatically acquiring knowledge structures that can assist a user in navigating through a document collection. Query log analysis has emerged as one of the most promising research areas to automatically derive such structures. We explore a biologically inspired model based on ant colony optimisation applied to query logs as an adaptive learning process that addresses the problem of deriving query suggestions. A user interaction with the search engine is treated as an individual ant’s journey and over time the collective journeys of all ants result in strengthening more popular paths which leads to a corresponding term association graph that is used to provide query modification suggestions. This association graph is being updated in a continuous learning cycle. In this paper we use a novel automatic evaluation framework based on actual query logs to explore the effect of different parameters in the ant colony optimisation algorithm on the performance of the resulting adaptive query suggestion model. We also use the framework to compare the ant colony approach against a state-of-the-art baseline. The experiments were conducted with query logs collected on a university search engine over a period of several years.

Keywords

User Session Query Suggestion Pheromone Level Mean Reciprocal Rank Interactive Search 
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 2011

Authors and Affiliations

  • M-Dyaa Albakour
    • 1
  • Udo Kruschwitz
    • 1
  • Nikolaos Nanas
    • 2
  • Dawei Song
    • 3
  • Maria Fasli
    • 1
  • Anne De Roeck
    • 4
  1. 1.University of EssexColchesterUK
  2. 2.Centre for Research and TechnologyThessalyGreece
  3. 3.Robert Gordon UniversityAberdeenUK
  4. 4.Open UniversityMilton KeynesUK

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