基于领域本体的语义查询扩展

在信息检索研究领域,资源与查询词的匹配决定信息检索质量。现有检索方法的检索结果存在过多不相关信息,不能很好满足用户需求。针对传统信息检索存在的问题与当前语义查询扩展方法的特点,本文在分析各种语义查询扩展方法及其相关研究的基础上,提出一种改进的基于领域本体的语义查询扩展方法。该方法论通过本体模型和概念相似度的计算对检索信息进行检索意图树的构建并扩展;然后在资源本体中以最短路径的方式搜索资源。实验结果表明,本文方法相较其他查询扩展方法能得到更好的检索结果。

Semantic Query Expansion Based on Domain Ontology

In the field of information retrieval,the match between resources and query words determines retrieval quality.The search results using current query methods exist too much irrelevant information and cannot satisfy customer needs.Considering the defects of traditional information retrieval and current feature of semantic query expansion,an improved ontology-based semantic query expansion method based on the analysis of various query expansion algorithms and related research has been proposed.The method constructs and expands the user search tree according to the query message basing on the ontology model and concept similarity computation.The experiment results show that the method can get better query results comparing to other query expansion method.