Query Expansion Model Based on Semi-Supervised Learning
基于半监督学习的查询扩展模型

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.