Text Classification Aided Job Opportunity Mining

摘要：

In this paper, we propose a novel framework to segment Chinese words, generate word vectors, train the corpus and make prediction. Based on the text classification technology, we successfully help the Chinese disabled persons to acquire job opportunities efficiently in real word. The results show that using this method to build the classifier yields better results than traditional methods. We also experimentally show that careful selection of a subset of features to represent the documents can improve the performance of the classifiers.

关键词： word segmentation SVM TF1DF word vector

作者: Shilin Zhang Hui Wang

作者单位: Faculty of Computer Science, Network and Informatioi Management Center North China University of Tec Faculty of Computer Science, Network and Information Management Center North China University of Tec

会议类型: 国际会议

会议名称: 2011 International Conference on Communication and Electronics Information(ICCEI 2011)(2011年通信和电子信息国际会议)

会议地点: 海口

会议语种:英文

页码: 6-9

在线出版日期: 2011-02-22（万方平台首次上网日期，不代表论文的发表时间）