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tc-dca: a system for text classification based on document's content allocation
Li Wenbo; Sun Le; Zhang Zhenzhong; Jiang Xue; Zhang Weiru
2010
Conference Name19th International Conference on Information and Knowledge Management and Co-located Workshops, CIKM'10
SourceInternational Conference on Information and Knowledge Management, Proceedings
Pages1937-1938
Conference Date40842
Conference PlaceToronto, ON, Canada
Indexed TypeEI
Publish PlaceUnited States
ISBN9781450000000
Department(1) Institute of Software, Chinese Academy of Sciences, 4# South Fourth Street, Zhong Guan Cun, Beijing, China
English AbstractThe text classification methods heavily depend on machine learning algorithms with abstract mathematic metrics, which obstruct the direct observation and intuitive understanding of the text-specific classification. In this paper, we model a document as a Document-Classes-Topics top-down hierarchical structure. Furthermore, by running the document generation procedure, we can obtain each class's content share, which not only can be used to make the classification decision but also can provide a natural visualization approach for text classification. We implement this idea by a new tool named TC-DCA, which provides the visualization of text classification result, where the target document is expressed graphically as its content's allocation on every class. TC-DCA can also perform the drilling down operation to reveal the classification effect of each word of the document.
KeywordKnowledge Management Learning Algorithms Text Processing Visualization
SponsorshipACM SIGIR; ACM SIGWEB; ACM SIGKDD
Content Type会议论文
URIhttp://ir.iscas.ac.cn/handle/311060/8928
Collection基础软件国家工程研究中心
Recommended Citation
GB/T 7714
Li Wenbo,Sun Le,Zhang Zhenzhong,et al. tc-dca: a system for text classification based on document's content allocation[C]. United States,2010:1937-1938.
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