TB-Structure: Collective Intelligence for Exploratory Keyword Search

  • Vagan Terziyan
  • Mariia GoloviankoEmail author
  • Michael Cochez
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10151)


In this paper we address an exploratory search challenge by presenting a new (structure-driven) collaborative filtering technique. The aim is to increase search effectiveness by predicting implicit seeker’s intents at an early stage of the search process. This is achieved by uncovering behavioral patterns within large datasets of preserved collective search experience. We apply a specific tree-based data structure called a TB (There-and-Back) structure for compact storage of search history in the form of merged query trails – sequences of queries approaching iteratively a seeker’s goal. The organization of TB-structures allows inferring new implicit trails for the prediction of a seeker’s intents. We used experiments to demonstrate both: the storage compactness and inference potential of the proposed structure.


Keyword search Query trail TB-structure Collective intelligence 



This article is based upon work from COST Action KEYSTONE IC1302, supported by COST (European Cooperation in Science and Technology).


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Vagan Terziyan
    • 1
  • Mariia Golovianko
    • 2
    Email author
  • Michael Cochez
    • 1
    • 3
    • 4
  1. 1.Faculty of Information TechnologyUniversity of JyvaskylaJyvaskylaFinland
  2. 2.Department of Artificial IntelligenceKharkiv National University of RadioelectronicsKharkivUkraine
  3. 3.Fraunhofer Institute for Applied Information Technology FITSankt AugustinGermany
  4. 4.Informatik 5RWTH Aachen UniversityAachenGermany

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