Wen JR, Nie JY, Zhang HJ "Query clustering using user logs" ACM TRANSACTIONS ON INFORMATION SYSTEMS 20 (1): 59-81 JAN 2002

[Eugene Garfield]

J.R. Wen  : jrwen at microsoft.com
J.Y. Nie    :  nie at iro.umontreal.ca
H.J.Zhang : hjzhang at microsoft.com



TITLE Query clustering using user logs
AUTHOR Wen JR, Nie JY, Zhang HJ
JOURNAL ACM TRANSACTIONS ON INFORMATION SYSTEMS  20 (1): 59-81 JAN 2002

 Document type: Article    Language: English    Cited References: 21
Times Cited: 0


Abstract:
Query clustering is a process used to discover frequently asked questions or
most popular topics on a search engine. This process is crucial for search
engines based on question-answering. Because of the short lengths of
Queries, approaches based on keywords are not suitable for query clustering.
This paper describes a new query clustering method that makes use of user
logs which allow us to identify the documents the users have selected for a
query. The similarity between two queries may be deduced from the common
documents the users selected for them. Our experiments show that a
combination of both keywords and user logs is better than using either
method alone.

Author Keywords:
algorithms, experimentation, performance, query clustering, web data mining,
user log, search engine

Addresses:
Wen JR, Microsoft Res, Beijing Sigma Ctr 49, Asia 5F,Zhichun Rd, Beijing,
Peoples R China
Microsoft Res, Beijing Sigma Ctr 49, Beijing, Peoples R China
Univ Montreal, Dept Informat & Rech Operat, Montreal, PQ H3C 3J7, Canada

Publisher:
ASSOC COMPUTING MACHINERY, NEW YORK

IDS Number:
517AE

ISSN:
1046-8188

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