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Time-Aware Diversifed Query Suggestion
Zhang XJ(张晓娟)2; Peng L(彭琳)1
2018-06
Conference NameThe ACM/IEEE Joint Conference on Digital Libraries in 2018
Source PublicationThe ACM/IEEE Joint Conference on Digital Libraries in 2018
Volume978-1-4503-5178-2/18/06
Issue978-1-4503-5178-2/18/06
Conference Date6月3-7日
Conference PlaceFort Worth, TX, USA
Author of SourceACM
Publication PlaceNew York
PublisherACM
Abstract

In this paper, we study query suggestion diversifcation for timeaware queries, where query suggestions are diversifed from multiple dimensions (e.g., topic and time). More precisely, we introduce the method of Time-aware Diversifed Query Suggestion (TDQS) which ensures that the generated suggested queries indicate possible time points in which a searcher who issued the original query may be interested. Preliminary experiments on AOL query log demonstrate that our proposed method can signifcantly improve the diversity and relevance effectiveness for time-aware queries in comparison with two state-of-the-art methods.
 

KeywordTime Diversifcation Query Suggestion
DOI10.1145/3197026.3203901
URL查看原文
Indexed ByIC
Language英语
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Document Type会议论文
Identifierhttp://ir.las.ac.cn/handle/12502/10258
Collection中国科学院文献情报中心(北京)_编辑出版中心
Corresponding AuthorZhang XJ(张晓娟)
Affiliation1.西南大学计算机与信息科学学院
2.中国科学院文献情报中心《数据智能(英文)》编辑部
First Author Affilication中国科学院文献情报中心
Corresponding Author Affilication中国科学院文献情报中心
Recommended Citation
GB/T 7714
Zhang XJ,Peng L. Time-Aware Diversifed Query Suggestion[C]//ACM. New York:ACM,2018.
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