基于广义内容概率潜在语义分析模型的推荐

doi:10.3724/SP.J.1087.2013.01330

计算机应用 ›› 2013, Vol. 33 ›› Issue (05): 1330-1333.DOI: 10.3724/SP.J.1087.2013.01330

基于广义内容概率潜在语义分析模型的推荐

张伟¹,黄炜²,夏利民¹

1. 中南大学信息科学与工程学院，长沙 410075
2. 长沙航空职业技术学院计算机系，长沙 410124

收稿日期:2012-11-01 修回日期:2013-01-01 出版日期:2013-05-01 发布日期:2013-05-08
通讯作者: 张伟
作者简介:张伟(1972-),男,黑龙江哈尔滨人，博士研究生,主要研究方向:模式识别、计算视觉；黄炜(1972-)，女，湖南长沙人，讲师,硕士,主要研究方向:数据挖掘；夏利民(1963-)，男，湖南长沙人，教授，博士生导师，博士,主要研究方向:模式识别、计算视觉。
基金资助:
教育部博士点基金资助项目(200805330059,20090162110057);湖南省科技计划项目(2011GK3213)

Recommendation research based on general content probabilistic latent semantic analysis model

ZHANG Wei¹,HUANG Wei²,XIA Limin¹

1. School of Information Science and Engineering, Central South University, Changsha Hunan 410075, China
2. Department of Computer Engineering, Changsha Aeronautical Vocational and Technical College, Changsha Hunan 410124, China

Received:2012-11-01 Revised:2013-01-01 Online:2013-05-08 Published:2013-05-01
Contact: ZHANG Wei

摘要/Abstract

摘要： 针对推荐系统中存在新项目及准确性难以把握等问题，提出一种基于广义内容概率潜在语义模型的推荐方法。该方法以概率潜在语义模型为基础，引入两组潜在变量及项目特征来建立广义内容概率潜在语义模型。该模型中两组潜在变量分别表示用户群体和项目群体，项目特征根据实际情况以特征词的形式进行表示，且通过不对称学习算法完成未知参数的训练及预测。利用三个不同的数据集对所提方法进行实验验证，结果表明该方法具有良好的项目推荐品质。

关键词: 概率潜在语义, 项目特征, 最大期望算法, 潜在变量, 项目推荐

Abstract: In the recommendation system, some new items and the accuracy issue cannot be well controlled. Therefore, a new recommendation method based on general content Probabilitistic Latent Semantic Analysis (PLSA) model was proposed. The general content PLSA model contained two latent variables indicating the user groups and item groups, and contained features of items that were trained by asymmetric learning algorithm. The experimental results show that the new method has good quality for recommendation on three different data sets.

Key words: Probabilitistic Latent Semantic Analysis (PLSA), item feature, Expectation-Maximization (EM) algorithm, latent variable, item recommendation

中图分类号:

TP391.41

张伟黄炜夏利民. 基于广义内容概率潜在语义分析模型的推荐[J]. 计算机应用, 2013, 33(05): 1330-1333.

ZHANG Wei HUANG Wei XIA Limin. Recommendation research based on general content probabilistic latent semantic analysis model[J]. Journal of Computer Applications, 2013, 33(05): 1330-1333.

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基于广义内容概率潜在语义分析模型的推荐

Recommendation research based on general content probabilistic latent semantic analysis model

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