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a unified graph-based iterative reinforcement approach to personalized search
Huang Yunping; Sun Le; Wang Zhe
2009
Conference Name5th Asia Information Retrieval Symposium
SourceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages193-204
Conference DateOCT 21-23,
Conference PlaceSapporo, JAPAN
Indexed Type其他
Publish PlaceHEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY
PublisherINFORMATION RETRIEVAL TECHNOLOGY, PROCEEDINGS
ISSN0302-9743
ISBN978-3-642-04768-8
DepartmentHuang, Yunping; Sun, Le; Wang, Zhe Chinese Acad Sci, Inst Software, Beijing 100190, Peoples R China.
English AbstractGeneral information retrieval systems do not perform well in satisfying users individual information need. This paper proposes a novel graph-based approach based on the following three kinds of mutual reinforcement relationships: RR-Relationship (Relationship among search results), RT-Relationship (Relationship between search results and terms), TT-Relationship (Relationship among terms). Moreover, the implicit feedback information, such as query logs and immediately viewed documents, can be utilized by this graph-based model. Our approach produces better ranking results and a better query model mutually and iteratively. Then a greedy algorithm concerning the diversity of the search results is employed to select the recommended results. Based on this approach, we develop an intelligent client-side web search agent GBAIR, and web search based experiments show that the new approach can improve search accuracy over another personalized web search agent.
KeywordInformation Retrieval
Language英语
Content Type会议论文
URIhttp://ir.iscas.ac.cn/handle/311060/8286
Collection基础软件国家工程研究中心
Recommended Citation
GB/T 7714
Huang Yunping,Sun Le,Wang Zhe. a unified graph-based iterative reinforcement approach to personalized search[C]. HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY:INFORMATION RETRIEVAL TECHNOLOGY, PROCEEDINGS,2009:193-204.
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