Improving Patent Search by Search Result Diversification

Abstract

Patent retrieval has some unique features relative to web search. One major task in this domain is finding existing patents that may invalidate new patents, known as prior-art or invalidity search, where search queries can be formulated from query patents (i.e., new patents). Since a patent document generally contains long and complex descriptions, generating effective search queries can be complex and difficult. Typically, these queries must cover diverse aspects of the new patent application in order to retrieve relevant documents that cover the full scope of the patent. Given this context, search diversification techniques can potentially improve the retrieval performance of patent search by introducing diversity into the document ranking. In this paper, we examine the effectiveness for patent search of a recent term-based diversification framework. Using this framework involves developing methods to identify effective phrases related to the topics mentioned in the query patent. In our experiments, we evaluate our diversification approach using standard measures of retrieval effectiveness and diversity, and show significant improvements relative to state-of-the-art baselines.