Microblog Query Expansion Based on Ontology Expansion and Borda Count Rank

摘要

Most of the traditional microblog query methods based on keywords matching lead to low query efficiency. It is difficult for users to get the real information they want without using the semantic expansion. With the study of microblog query expansion algorithm based on ontology and local query feedback, in this paper, we propose a microblog query expansion algorithm based on ontology expansion and Borda count rank. We use the semantic connection provided by ontology knowledge base to expand the initial query words, combine the local query feedback to filter the final query expansion words, and use Borda count method to rearrange the query results. The experimental results show that Microblog query expansion algorithm based on ontology expansion and Borda count rank has better recall and precision rate than keyword-based query expansion algorithm, ontology-based query expansion algorithm and query expansion algorithm based on ontology and local query feedback.