Patent Retrieval: A Literature Review

TL;DR

This review discusses the challenges and recent advances in Patent Retrieval, emphasizing the need for domain-specific adaptation, interactive tools, and highlighting future research directions in patent analysis tasks.

Contribution

It provides a comprehensive overview of current PR methods, identifies limitations in recall performance, and suggests the development of interactive tools tailored for patent professionals.

Findings

State-of-the-art automatic PR has average recall performance.

Domain adaptation is crucial for effective patent retrieval.

Interactive search tools can assist patent professionals effectively.

Abstract

With the ever increasing number of filed patent applications every year, the need for effective and efficient systems for managing such tremendous amounts of data becomes inevitably important. Patent Retrieval (PR) is considered the pillar of almost all patent analysis tasks. PR is a subfield of Information Retrieval (IR) which is concerned with developing techniques and methods that effectively and efficiently retrieve relevant patent documents in response to a given search request. In this paper we present a comprehensive review on PR methods and approaches. It is clear that, recent successes and maturity in IR applications such as Web search cannot be transferred directly to PR without deliberate domain adaptation and customization. Furthermore, state-of-the-art performance in automatic PR is still around average in terms of recall. These observations motivate the need for interactive search tools which provide cognitive assistance to patent professionals with minimal effort. These tools must also be developed in hand with patent professionals considering their practices and expectations. We additionally touch on related tasks to PR such as patent valuation, litigation, licensing, and highlight potential opportunities and open directions for computational scientists in these domains.