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Title:
Diversifying Tag Selection Result for Tag Clouds by Enhancing both Coverage and Dissimilarity
Author: Wang, Meiling ; Zhou, Xiang ; Tao, Qiuming ; wu, Wei ; Zhao, Chen
Conference Name: 14th International Conference on Web Information Systems Engineering (WISE)
Conference Date: OCT 13-15, 2013
Issued Date: 2013
Conference Place: Nanjing, PEOPLES R CHINA
Keyword: Tag Cloud ; Tag Selection ; Result Diversification ; Coverage ; Dissimilarity ; Submodularity ; Greedy Algorithm
Publish Place: SPRINGER-VERLAG BERLIN
Indexed Type: CPCI
ISSN: 0302-9743
ISBN: 978-3-642-41154-0; 978-3-642-41153-3
Department: [Wang, Meiling; Zhou, Xiang; Tao, Qiuming; wu, Wei; Zhao, Chen] Chinese Acad Sci, Inst Software, Beijing, Peoples R China.
Abstract: Tag cloud has been a popular facility used by social sites for online resource summarization and navigation. Tag selection, which aims to select a limited number of representative tags from a large set of tags, is the core task for creating tag clouds. Diversity of tag selection result is an important factor that affects user satisfaction. Information coverage and item dissimilarity are two major perspectives for exploring the concept of diversity, while existing tag selection approaches usually consider diversification from single perspective. In this paper, we propose a new approach for diversifying tag selection result, which takes into account both information coverage and tag dissimilarity. We design two sub-objective functions about information coverage and tag dissimilarity, respectively, and construct an objective function as a convex combination of the two sub-objective ones. We also give out a greedy algorithm that can well approximate the objective function. We conduct experiments on 17 datasets extracted from the website of CiteULike to compare our approach with existing ones. The experiment results show that our approach can achieve promising performance of diversification.
English Abstract: Tag cloud has been a popular facility used by social sites for online resource summarization and navigation. Tag selection, which aims to select a limited number of representative tags from a large set of tags, is the core task for creating tag clouds. Diversity of tag selection result is an important factor that affects user satisfaction. Information coverage and item dissimilarity are two major perspectives for exploring the concept of diversity, while existing tag selection approaches usually consider diversification from single perspective. In this paper, we propose a new approach for diversifying tag selection result, which takes into account both information coverage and tag dissimilarity. We design two sub-objective functions about information coverage and tag dissimilarity, respectively, and construct an objective function as a convex combination of the two sub-objective ones. We also give out a greedy algorithm that can well approximate the objective function. We conduct experiments on 17 datasets extracted from the website of CiteULike to compare our approach with existing ones. The experiment results show that our approach can achieve promising performance of diversification.
Language: 英语
Content Type: 会议论文
URI: http://ir.iscas.ac.cn/handle/311060/16528
Appears in Collections:软件所图书馆_会议论文

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Recommended Citation:
Wang, Meiling,Zhou, Xiang,Tao, Qiuming,et al. Diversifying Tag Selection Result for Tag Clouds by Enhancing both Coverage and Dissimilarity[C]. 见:14th International Conference on Web Information Systems Engineering (WISE). Nanjing, PEOPLES R CHINA. OCT 13-15, 2013.
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