TB-structure: Collective intelligence for exploratory keyword search

Vagan Terziyan, Mariia Golovianko*, Michael Cochez

*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

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.

Original languageEnglish
Title of host publicationSemantic Keyword-Based Search on Structured Data Sources - COST Action IC1302 2nd International KEYSTONE Conference, IKC 2016, Revised Selected Papers
EditorsAndrea Cali, Dorian Gorgan, Martin Ugarte
PublisherSpringer Verlag
Pages171-178
Number of pages8
ISBN (Print)9783319536392
DOIs
Publication statusPublished - 1 Jan 2017
Externally publishedYes
Event2nd COST Action IC1302 International KEYSTONE Conference on Semantic Keyword-Based Search on Structured Data Sources, IKC 2016 - Cluj-Napoca, Romania
Duration: 8 Sep 20169 Sep 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10151 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference2nd COST Action IC1302 International KEYSTONE Conference on Semantic Keyword-Based Search on Structured Data Sources, IKC 2016
CountryRomania
CityCluj-Napoca
Period8/09/169/09/16

Keywords

  • Collective intelligence
  • Query trail
  • Search
  • TB-structure

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