基于自动查询扩展的专利文档检索方法

Existing patent retrieval methods cannot effectively capture user's query intents due to the lack in query expansion. To solve this problem, this paper propose a novel patent retrieval method based on automatic query expansion. Considering the characteristics of patent documents, an improved TF-IDF scheme is first adopted to extract patent domain terms and build the domain vocabularies. At the retrieval stage, query inputs are analyzed to extract key words, and then the field of query and the difficulty of query expansion are determined based on domain vocabularies. Furthermore, according to the term distribution variation analysis on pseudo related documents, the pseudo relevance feedback (PRF)-based automatic query expansion techniques are utilized to generate and rank the candidate expansion terms. At last, the expansion terms are combined with original query conditions to compose the final query conditions for searching. The comparative experiment results show that our method achieves better recall and average precision.