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Desktop Data Driven Approach to Personalize Query Recommendation

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成果类型:
期刊论文、会议论文
作者:
Li, Xiao-yun;Yu, Ying*
通讯作者:
Yu, Ying
作者机构:
[Li, Xiao-yun; Yu, Ying] Univ South China, Sch Comp Sci & Technol, Hengyang, Hunan, Peoples R China.
通讯机构:
[Yu, Ying] U
Univ South China, Sch Comp Sci & Technol, Hengyang, Hunan, Peoples R China.
语种:
英文
关键词:
Desktop data;Query recommendation;Search task;User model;Work task
期刊:
Communications in Computer and Information Science
ISSN:
1865-0929
年:
2017
卷:
727
期:
1
页码:
100-109
会议名称:
The Third International Conference of Pioneering Computer Scientists, Engineers and Educators,ICPCSEE 2017(originally ICYCSEE)
会议时间:
2017-09-22
会议地点:
中国湖南长沙
基金类别:
Acknowledgements. This work is supported by the National Natural Science Foundation of China (No. 61402220), Scientific Research Project of Education Bureau of Hunan Province, China (Grant No. 15C1186), the Construct Program for the Key Discipline in University of South China (No. NHxk02), the Construct Program for Innovative Research Team in University of South China.
机构署名:
本校为第一且通讯机构
院系归属:
计算机科学与技术学院
摘要:
Query recommendation is an effective method to help users describe their search intentions. In a personalized system, cold-start and the data sparsity were unavoidable, which directly lead to deficient performance of personalizing. As a significant part of a user’s personal information space, a personal computer owns lots of documents relevant to his or her interest. Therefore, desktop data was introduced to construct a user’s preference model. Furthermore, considering the variety of desktop data, relationship between search task and work task was simultaneously exploited to predic...

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