LDA based Related Word Detection in Advertising

摘要：

In this paper, we propose a new method for related word detection in Advertising by combining LDA topic model and word co-occurrence. We use a corpus of BaiduBaike, which is a Chinese Encyclopedia, to calculate the word co-occurrence. Words allocation on topics driven by LDA is used to sort the related words glossary which is obtained by the traditional cooccurrence procedure. We evaluate our method on advertising related word recognition, and the experiments result shows that the method is feasible.

关键词： Related Words LDA Similarity Advertising Context Entropy

作者: Xin Jin Huan Xia Juanzi Li

作者单位: Department of Computer Science & Technology Tsinghua University Beijing 100084

会议类型: 国际会议

会议名称: 2010 Seventh Web Information System and Applications Conference(第七届全国web信息系统及其应用学术会议)

会议地点: 呼和浩特

会议语种:英文

页码: 90-94

在线出版日期: 2010-08-20（万方平台首次上网日期，不代表论文的发表时间）