中文摘要：

针对现有信息检索系统查询性能的不足，提出了一种结合相关规则和WordNet本体信息的查询扩展方法。该方法借助相关规则挖掘和WordNet本体信息构建加权词语关系图，并根据加权图的结构和权重信息计算扩展词的重要性。查询时，从这个图中取原查询词的最邻近词作为扩展词来源，选取其中权重最大的P个词返回并进行二次检索。在实现算法的基础上，通过Lucene全文检索器进行实验，将所得的结果值F1与其他算法的结果作比较。比较结果表明，该方法比不作扩展的检索有约16．93％的性能提升。

英文摘要：

Against the shortage of the query performance of information retrieval system, this paper proposed a query expan- sion method based on the integration of correlation rules and WordNet ontology. This method used correlation rule mining and WordNet ontology to build a weighted word graph. It calculated the importance of each word according to the graph structure and the weights. In the query stage, it selected the neighbor words of original query as the expansion word source, and then used the top p words with maximum weights for second retrieval. On the basis of the algorithm implemention, it used a full-text search machine Lucene to do experiment. At last, it compared the proposed method results F1 values with the other algorithms. Experimental results demonstrate that the proposed approach achieves 16.93% retrieval improvement compared with the meth- od without query expansion.