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Title:
a novel kernel for text categorization
Author: Zhang Lujiang ; Hu Xiaohui
Source: CSAE 2012 - Proceedings, 2012 IEEE International Conference on Computer Science and Automation Engineering
Conference Name: 2012 IEEE International Conference on Computer Science and Automation Engineering, CSAE 2012
Conference Date: May 25, 2012 - May 27, 2012
Issued Date: 2012
Conference Place: Zhangjiajie, China
Keyword: Algorithms ; Computer science ; Support vector machines
Indexed Type: EI
ISBN: 9781467300865
Department: (1) School of Automation Science and Electrical Engineering Beijing University of Aeronautics and Astronautics Beijing 100191 China; (2) Institute of Software Chinese Academy of Sciences Beijing 100190 China
Sponsorship: IEEE Beijing Section; Hunan University of Humanities, Science and Technology; Tongji University; Xiamen University; Central South University
Abstract: In this paper we proposed a novel kernel for text categorization. This kernel is an inner product in the feature space generated by all word combinations of specified length. A word combination is a collection of different words co-occurring in the same sentence. The word combination of length k is weighted by the k-th root of the product of the inverse document frequencies (IDF) of its words. A computationally simple and efficient algorithm was proposed to calculate this kernel. We conducted experiments on the 20 Newsgroups dataset. This kernel achieves better performance than the classical word kernel and word-sequence kernel. We also assessed the impact of word combination length on performance. © 2012 IEEE.
English Abstract: In this paper we proposed a novel kernel for text categorization. This kernel is an inner product in the feature space generated by all word combinations of specified length. A word combination is a collection of different words co-occurring in the same sentence. The word combination of length k is weighted by the k-th root of the product of the inverse document frequencies (IDF) of its words. A computationally simple and efficient algorithm was proposed to calculate this kernel. We conducted experiments on the 20 Newsgroups dataset. This kernel achieves better performance than the classical word kernel and word-sequence kernel. We also assessed the impact of word combination length on performance. © 2012 IEEE.
Language: 英语
Content Type: 会议论文
URI: http://ir.iscas.ac.cn/handle/311060/15762
Appears in Collections:软件所图书馆_会议论文

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Recommended Citation:
Zhang Lujiang,Hu Xiaohui. a novel kernel for text categorization[C]. 见:2012 IEEE International Conference on Computer Science and Automation Engineering, CSAE 2012. Zhangjiajie, China. May 25, 2012 - May 27, 2012.
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