Diving into Knowledge Graphs for Patents: Open Challenges and Benefits

Abstract

Textual documents are the means of sharing information and preserving knowledge for a large variety of domains. The patent domain is also using such a paradigm which is becoming difficult to maintain and is limiting the potentialities of using advanced AI systems for domain analysis. To overcome this issue, it is more and more frequent to find approaches to transform textual representations into Knowledge Graphs (KGs). In this position paper, we discuss KGs within the patent domain, present its challenges, and envision the benefits of such technologies for this domain. In addition, this paper provides insights of such KGs by reproducing an existing pipeline to create KGs and applying it to patents in the computer science domain.