A Query Reformulation Model Using Markov Graphic Method

Information retrieval model is still can not achieve satisfactory performance after decades of development. One of the reasons is the queries can not express information need precisely. Researches have shown that query reformulation can improve the performance of retrieval model. In this paper, we propose a query reformulation model, which use Markov network to represent term relationship to obtain useful information from corpus to reformulate query. Experimental results show that our model can avoid topic drift and then improve the retrieval performance.