Query expansion model based on interest ontology

In this paper, we present a query expansion model based on interest ontology and its application in the e-government domain. Traditional keyword searching is processed by short queries posed by users to vaguely describe their information need but with poor retrieval performance. So we propose an interest ontology-based query expansion semantic retrieval model. In this model, we build the user´s interest ontology; propose a concept similarity computation algorithm to add relevant concepts to original query set. Furthermore, we verify the feasibility of the algorithm by some experiments. The experimental results show that the model can improve the precision and recall compared with traditional method. Although the model presented here is used to retrieve sensitive information in e-government domain, it is applicable to other domain.