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New Technology of Library and Information Service  2014, Vol. 30 Issue (4): 34-40    DOI: 10.11925/infotech.1003-3513.2014.04.06
Current Issue | Archive | Adv Search |
Query Recommendation Based on User Task
Zhang Xiaojuan, Tang Xiangbin
Center for the Studies of Information Resources, Wuhan University, Wuhan 430072, China
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Abstract  

[Objective] This paper tries to realize user task-oriented query suggestion from session level based on AOL query log dataset. [Methods] This paper firstly measures the relationship between queries based on user task, and then realizes user task-oriented query recommendation by exploiting random walk to traversal graph model. [Results] The final results show that our query recommendation method outperforms that method which measures relationship between queries by exploiting queries occurrence information. [Limitations] Misspelled candidate queries are not implemented spell correction; Query recommendation are not realized from query level; The recommendation effect of rare queries and ambiguous queries are not good. [Conclusions] Measuring the relationship between queries based on user task can improve the performance of query recommendation.
Key words： Query recommendation      User task      Query log     
Received: 17 December 2013      Published: 19 May 2014
:  G353.4  
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Zhang Xiaojuan, Tang Xiangbin. Query Recommendation Based on User Task. New Technology of Library and Information Service, 2014, 30(4): 34-40.

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https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2014.04.06     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2014/V30/I4/34

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