Publication: Using Monte-Carlo simulation for automatic new topic identification of search engine transaction logs
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Date
2007
Authors
Özmutlu, Seda
Özmutlu, Hüseyin Cenk
Büyük, Buket
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
IEEE
Abstract
One of the most important dimensions of search engine user information seeking behavior and search engine research is content-based behavior, and limited research has focused on content-based behavior of search engine users. The purpose of this study is to present a simulation application on information science, by performing automatic new topic identification in search engine transaction logs using Monte Carlo simulation. Sample data logs from FAST and Excite are used in the study. Findings show that Monte Carlo simulation for new topic identification yields satisfactory results in terms of identifying topic continuations, however the performance measures regarding topic shifts should be improved.
Description
Bu çalışma, 09-12, Aralık 2007 tarihlerinde Washington[Amerika]’da düzenlenen 2007 Winter Simulation Conference Kongresi‘nde bildiri olarak sunulmuştur.
Keywords
Information-seeking, Computer software, Engines, Information management, Information services, World Wide Web, Internet, Telecommunication networks, Monte Carlo methods, Search engines, Content-based, User information, Engine research, Topic identification, Monte Carlo Simulation, Simulation applications, Monte-Carlo simulations, Sample data, Performance measures, Information retrieval
Citation
Özmutlu, S. vd. (2007). "Using Monte-Carlo simulation for automatic new topic identification of search engine transaction logs". Proceedings - Winter Simulation Conference, 2285-2293.