Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
493734 | Simulation Modelling Practice and Theory | 2008 | 20 Pages |
Abstract
One of the most important dimensions of Web 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 perform 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.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Seda Ozmutlu, Huseyin C. Ozmutlu, Buket Buyuk,