Subject categorization of query terms for exploring web users' search interests

Hsiao Tieh Pu*, Shui Lung Chuang, Chyan Yang

*此作品的通信作者

研究成果: 雜誌貢獻期刊論文同行評審

75 引文 斯高帕斯(Scopus)

摘要

Subject content analysis of Web query terms is essential to understand Web searching interests. Such analysis includes exploring search topics and observing changes in their frequency distributions with time. To provide a basis for in-depth analysis of users' search interests on a larger scale, this article presents a query categorization approach to automatically classifying Web query terms into broad subject categories. Because a query is short in length and simple in structure, its intended subject(s) of search is difficult to judge. Our approach, therefore, combines the search processes of real-world search engines to obtain highly ranked Web documents based on each unknown query term. These documents are used to extract cooccurring terms and to create a feature set. An effective ranking function has also been developed to find the most appropriate categories. Three search engine logs in Taiwan were collected and tested. They contained over 5 million queries from different periods of time. The achieved performance is quite encouraging compared with that of human categorization. The experimental results demonstrate that the approach is efficient in dealing with large numbers of queries and adaptable to the dynamic Web environment. Through good integration of human and machine efforts, the frequency distributions of subject categories in response to changes in users' search interests can be systematically observed in real time. The approach has also shown potential for use in various information retrieval applications, and provides a basis for further Web searching studies.

原文英語
頁(從 - 到)617-630
頁數14
期刊Journal of the American Society for Information Science and Technology
53
發行號8
DOIs
出版狀態已發佈 - 2002 六月

ASJC Scopus subject areas

  • 軟體
  • 資訊系統
  • 人機介面
  • 電腦網路與通信
  • 人工智慧

指紋

深入研究「Subject categorization of query terms for exploring web users' search interests」主題。共同形成了獨特的指紋。

引用此