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New Technology of Library and Information Service  2008, Vol. 24 Issue (7): 47-53    DOI: 10.11925/infotech.1003-3513.2008.07.10
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Study on the Characters of Language Used in Web Searching
Lai Maosheng  Qu Peng
(Department of Information Management, Peking University, Beijing 100871, China)
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This paper concerns on the characteristics of language used in the Web searching and seeks to make an exploratory study on the syntax and semantic query problems. The research mainly uses search engine query log analysis method, then compares with the results from Web questionnaire analysis. At last, the authors come to the conclusion on the characteristics of syntax, term category, assistant words, and principal words. The syntax in Web searching is very stable; users rely greatly on assistant words; the natural-language-character of query is obvious; and the query syntax is very simple. Search engines has become an helpful supplement for traditional information retrieval tools; forms unique contents, in which consists mostly entertainment and non-mainstream culture, and which differentiate search engine from traditional information retrieval tools.

Key wordsRetrieval language      Searching      Log mining      User      Language usage     
Received: 07 March 2008      Published: 25 July 2008


Corresponding Authors: Lai Maosheng     E-mail:
About author:: Lai Maosheng,Qu Peng

Cite this article:

Lai Maosheng,Qu Peng. Study on the Characters of Language Used in Web Searching. New Technology of Library and Information Service, 2008, 24(7): 47-53.

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[1] 王继民, 陈翀, 彭波. 大规模中文搜索引擎的用户日志分析[J]. 华南理工大学学报(自然科学版), 2004, 32(S): 1-5.
[2] 王继民, 彭波. 搜索引擎用户访问量模型[J]. 计算机工程与应用, 2004, 40(25): 9-11,30.
[3] 王继民, 彭波. 搜索引擎用户点击行为分析[J]. 情报学报, 2006, 25(2): 154-162.
[4] 王继民, 孟涛. Web搜索引擎日志挖掘研究[R]. 中国人搜索行为研究实验室年度报告2006. 北京: 北京大学信息管理系, 2006: 35-48.
[5] Jansen B J, Spink A, Saracevic T. Real Life, Real Users, and Real Needs: A study and Analysis of User Queries on the Web[J]. Information Processing and Management, 2000, 36(2): 207-227.
[6] Spink A, Jansen B J, Koshman S. From E-sex to E-commerce: Web Search  Changes[J]. IEEE Computer, 2002, 35(3): 107-109.
[7] Spink A, Ozmutlu H C, Ozmutlu S. Multitasking Information Seeking and Searching Processes[J]. Journal of the American Society for Information Science and Technology, 2002, 53(8): 639-652.
[8] Ozmutlu S, Spink A, Ozmutlu H C. A Day in the Life of Web Searching: An Exploratory Study[J]. Information Processing and Management, 2004, 40(2):319-345.
[9] Jansen B J, Spink A. How are We Searching the World Wide Web? A Comparison of Nine Search EngineTtransaction Logs[J]. Information Processing and Management, 2006, 42(1):248-263.

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