Combination of multiple bipartite ranking for multipartite web content quality evaluation
文献类型：期刊论文
| 作者 | Jin, Xiao-Bo1; Geng, Guang-Gang2; Sun, Minghe3; Zhang, Dexian1 |
| 刊名 | Neurocomputing
 |
| 出版日期 | 2015-02-03 |
| 卷号 | 149页码:1305-1314 |
| 关键词 | Web content quality evaluation Multipartite ranking Bipartite ranking Encoding design Decoding design |
| ISSN号 | 0925-2312 |
| DOI | 10.1016/j.neucom.2014.08.067 |
| 通讯作者 | Geng, guang-gang(gengguanggang@cnnic.cn) |
| 英文摘要 | Web content quality evaluation is crucial to various web content processing applications. bagging has a powerful classification capacity by combining multiple classifiers. in this study, similar to bagging, multiple pairwise bipartite ranking learners are combined to solve the multipartite ranking problems for web content quality evaluation. both encoding and decoding mechanisms are used to combine bipartite rankers to form a multipartite ranker and, hence, the multipartite ranker is called multirank.ed. both binary encoding and ternary encoding extend each rank value to an l-1 dimensional vector for a ranking problem with l different rank values. predefined weighting and adaptive weighting decoding mechanisms are used to combine the ranking results of bipartite rankers to obtain the final ranking results. in addition, some theoretical analyses of the encoding and the decoding strategies in the multirank.ed algorithm are provided. computational experiments using the dc2010 datasets show that the combination of binary encoding and predefined weighting decoding yields the best performance in all four combinations. furthermore, this combination performs better than the best winning method of the dc2010 competition. (c) 2014 elsevier b.v. all rights reserved. |
| WOS关键词 | DOCUMENTS |
| WOS研究方向 | Computer Science |
| WOS类目 | Computer Science, Artificial Intelligence |
| 语种 | 英语 |
| WOS记录号 | WOS:000356105100018 |
| 出版者 | ELSEVIER SCIENCE BV |
| URI标识 | http://www.irgrid.ac.cn/handle/1471x/2374080 |
| 专题 | 计算机网络信息中心 |
| 通讯作者 | Geng, Guang-Gang |
| 作者单位 | 1.Henan Univ Technol, Sch Informat Sci & Engn, Zhengzhou 450001, Henan, Peoples R China 2.Chinese Acad Sci, Comp Network Informat Ctr, Beijing 100190, Peoples R China 3.Univ Texas San Antonio, Coll Business, San Antonio, TX 78249 USA |
| 推荐引用方式 GB/T 7714 | Jin, Xiao-Bo,Geng, Guang-Gang,Sun, Minghe,et al. Combination of multiple bipartite ranking for multipartite web content quality evaluation[J]. Neurocomputing,2015,149:1305-1314. |
| APA | Jin, Xiao-Bo,Geng, Guang-Gang,Sun, Minghe,&Zhang, Dexian.(2015).Combination of multiple bipartite ranking for multipartite web content quality evaluation.Neurocomputing,149,1305-1314. |
| MLA | Jin, Xiao-Bo,et al."Combination of multiple bipartite ranking for multipartite web content quality evaluation".Neurocomputing 149(2015):1305-1314. |
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来源：计算机网络信息中心
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