Complaint Text Classification Based on Guiding Words
Hu Juxiang1, Lv Xueqiang1, Liu Kehui2,3
1 Beijing Key Laboratory of Internet Culture and Digital Dissemination Research, Beijing Information Science and Technology University, Beijing 100101, China;
2 School of Management and Economics, Beijing Institute of Technology, Beijing 100081, China;
3 Beijing Research Center of Urban System Engineering, Beijing 100035, China
[Objective] For complaint text has the characteristics of informative, unstructured, weak regularity etc., the current information management of city complaint needs an efficient classification method to improve the efficiency of the management staff.[Methods] Analyze the characteristics of complaints and go for text preprocessing; Then use the parser, synonyms forest, and through the contribution of the document to filter guide word; At last, calculate the guide word weighting coefficients with TF-IDF, use VSM model to represent guide words and use SVM model to classify the complaint text. [Results] In multiple categories of complaint text, the average precision of the method is up to 82.1% and the average recall is up to 82.3%. [Limitations] Thesparsity of complaint text affects the classification results to a certain extent.[Conclusions] The experiment results show that the method is effective and feasible in the text classification of complaints, and it can improve categorization effect of thecomplaint text.
胡菊香, 吕学强, 刘克会. 利用类别引导词的投诉文本分类[J]. 现代图书情报技术, 2015, 31(7-8): 97-103.
Hu Juxiang, Lv Xueqiang, Liu Kehui. Complaint Text Classification Based on Guiding Words. New Technology of Library and Information Service, DOI：10.11925/infotech.1003-3513.2015.07.13.
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