Mixed Correlation Based Markov Network for Query Expansion in Information Retrieval
Shi Song · Zhongwen xinxi xuebao · 2013
Query expansion is effective to improve retrieval efficiency.In this paper,the mixed correlation between terms is quantized by term cliques which are obtained from Markov network,so as to solve the computation of the term relationship lack of cooccurence in corpus.The enhanced mixed correlation is then applied to query expansion.The experimental results show that the proposed method outperforms that based on direct correlation.In addition,the method is slightly better than a Markov network model based on cliques significantly reduces the computational overhead of term cliques.