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Received:July 01, 2011 Revised:September 01, 2011
Received:July 01, 2011 Revised:September 01, 2011
中文摘要: 查询扩展是针对信息检索中常见的“词不匹配”问题提出的一种优化方法。通过分析现有查询扩展方法的不足,提出一种基于半监督学习的查询扩展模型,该模型将查询扩展看作一个分类问题,并采用直推式支持向量机对样本进行训练。实验结果表明该方法进一步提高了搜索引擎的查全率和查准率。
Abstract:Query expansion is a optimization method for “word mismatch” issues in information retrieval domain. By analyzing the shortcomings of existing methods, query expansion model based on semi-supervised learning is proposed, the model seems query expansion as a classification problem, and using transductvie support vector machine to train the samples. Experiments show that the recall and precision rates of search engine are further improved by this method.
keywords: information retrieve query expansion transductive support vector machines semi-supervised learning SVM
文章编号： 中图分类号： 文献标志码：
基金项目:
| Author Name | Affiliation |
| SU Jun-Jie | Institute of Command and Technology of Equipment, Beijing 101416, China |
| CHEN Jun | Institute of Command and Technology of Equipment, Beijing 101416, China |
| Author Name | Affiliation |
| SU Jun-Jie | Institute of Command and Technology of Equipment, Beijing 101416, China |
| CHEN Jun | Institute of Command and Technology of Equipment, Beijing 101416, China |
引用文本：
苏俊杰,陈俊.基于半监督学习的查询扩展模型.计算机系统应用,2012,21(3):181-184
SU Jun-Jie,CHEN Jun.Query Expansion Model Based on Semi-Supervised Learning.COMPUTER SYSTEMS APPLICATIONS,2012,21(3):181-184
苏俊杰,陈俊.基于半监督学习的查询扩展模型.计算机系统应用,2012,21(3):181-184
SU Jun-Jie,CHEN Jun.Query Expansion Model Based on Semi-Supervised Learning.COMPUTER SYSTEMS APPLICATIONS,2012,21(3):181-184
