DEFINING TOPIC BOUNDARIES IN SEARCH ENGINE TRANSACTION LOGS USING GENETIC ALGORITHMS

ÖZMUTLU S., Cosar C. G.

APPLIED ARTIFICIAL INTELLIGENCE, vol.23, no.10, pp.910-931, 2009 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 23 Issue: 10
  • Publication Date: 2009
  • Doi Number: 10.1080/08839510903363446
  • Journal Name: APPLIED ARTIFICIAL INTELLIGENCE
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.910-931
  • Bursa Uludag University Affiliated: Yes

Abstract

This study proposes to use genetic algorithms for defining the topic boundaries in search of engine transaction logs. Users are interested in multiple topics during a search session, and genetic algorithms are used in this study to determine whether a search engine user has changed topics during a session. Sample data logs from FAST and Excite search engines were analyzed. The findings show that genetic algorithms are fairly successful in identifying topic continuations and shifts in search engine transaction logs.