Semantic Query Expansion based on Entity Association in Medical Question Answering

Abstract

Query expansion technology is a common method to solve the semantic deviation problem between questions and answers in the question answering system. In medical question answering field, the current semantic-based query expansion method has the following two shortcomings. (1) In the stage of obtaining candidate extended terms, only the medical entity’s concept in the query is used, but the medical entity’s association between questions and answers is ignored (2) During the extended terms filtering stage, the interference of negative medical entities to the mutual information is ignored. Given the above-mentioned deficiencies, this paper proposes a semantic query expansion method based on entity association in medical question answering. This method first combines the query intent with the inference association between medical entities to obtain candidate extended terms from the medical knowledge graph. Then filter candidate extended terms using the selection method based on negative medical entity recognition and mutual information and thus get the final extended terms according to the co-occurrence association between medical entities. Experimental results show that our proposed method outperforms the query expansion method based on the thesaurus which commonly used in the current medical question and answering system.