Automatic Web Image Selection with a Probabilistic Latent Topic Model

摘要：

We propose a new method to select relevant images to the given keywords from images gathered from theWeb based on the Probabilistic Latent Semantic Analysis (PLSA) model which is a probabilistic latent topic model originally proposed for text document analysis. The experimental results show that the results by the proposed method are almost equivalent to or outperform the results by existing methods. In addition, it is proved that our method can select more various images compared to the existing SVM-based methods.

关键词： Web image mining image recognition

作者: Keiji Yanai

作者单位: The University of Electro-Communications Chofu, Tokyo, 182-8585 JAPAN

会议类型: 国际会议

会议名称: 第十七届国际万维网大会(the 17th International World Wide Web Conference)(WWW08)

会议地点: 北京

会议语种:英文

在线出版日期: 2008-04-21（万方平台首次上网日期，不代表论文的发表时间）