Calculating the feature method of short text based on analytic hierarchy process |
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Authors: | Xue-qiang ZOU Xiu-guo BAO Xiao-jun HUANG Hong-yuan MA Qing-sheng YUAN |
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Affiliation: | 1. Institute of Information Engineering, Chinese Academy of Sciences, Beijing 100093, China;2. National Computer Network Emergency Response Technical Team/Coordination Center of China, Beijing 100029, China;3. University of Chinese Academy of Sciences, Beijing 100049, China;4. School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China |
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Abstract: | In order to model the accurate interest preference of microblog users and discover user groups with similar in-terest, a new method was proposed which considered the total amount of retweets, comments and attitudes of each mi-croblog for text feature calculation with utilizing classic analytical hierarchy process method. The proposed method used three indicators to evaluate the importance of the text feature representation and made an improvement on traditional tf-idf feature calculation method to fit for short text. Furthermore, this method was also implemented in the traditional clustering algorithm. Experimental results show that, compared with the traditional tf-idf method, the improved approach has a better clustering effect on the average scattering for clusters and the total separation between clusters. |
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Keywords: | analytic hierarchy process feature calculation text clustering short tex |
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