Prior-Art Relevance Ranking Based on the Examiner's Query Log Content

This work belongs to the domain of technical information retrieval (IR) and, more specifically, patent retrieval. We show that the recorded history of patent examiner’s search queries can be used to create a more effective method of finding prior art patents than search methods based on titles and claims. We verify the performance of the proposed method experimentally. Our experiments show that we can almost double the recall measure, compared to classical techniques based on titles and claims. The other contribution of our work is the creation of a database of over half a million patent examiners queries (recorded search activity over the patents prosecution process). The paper also discusses the limitations of the current work and the ongoing research to further improve the proposed approach.

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