Exploring Legal Patent Citations for Patent Valuation

Abstract

Effective patent valuation is important for patent holders. Forward patent citations, widely used in assessing patent value, have been considered as reflecting knowledge flows, just like paper citations. However, patent citations also carry legal implication, which is important for patent valuation. We argue that patent citations can either be technological citations that indicate knowledge transfer or be legal citations that delimit the legal scope of citing patents. In this paper, we first develop citation-network based methods to infer patent quality measures at either the legal or technological dimension. Then we propose a probabilistic mixture approach to incorporate both the legal and technological dimensions in patent citations, and an iterative learning process that integrates a temporal decay function on legal citations, a probabilistic citation network based algorithm and a prediction model for patent valuation. We learn all the parameters together and use them for patent valuation. We demonstrate the effectiveness of our approach by using patent maintenance status as an indicator of patent value and discuss the insights we learned from this study.

A Fast and Scalable Algorithm for Prior Art Search

“…Citations are among the relevant metadata for patents. Citations related to legal rights can be used for the PAS because they reflect the quality of a patent [39]. Furthermore, forward citations, although often classified as innovative or discontinuous concerning prior art, include the history of technical prior art [40].…”

Patent retrieval: a literature review

“…Citation analysis has been and still a main technique for patent valuation Trajtenberg (1990); Harhoff et al (1999); Hall et al (2005); Czarnitzki et al (2010); Wang et al (2014). Wang et al (2014) proposed a probabilistic mixture approach to predict whether a topic patent will be renewed at different renewal periods. The method first divides the citations into two groups; technological and legal.…”

Descubrimiento y evaluación de recursos web de calidad mediante Patent Link Analysis

“…S. Chen, Shih, & Chang, 2014;E. J. Han & Sohn, 2015;Hegde & Sampat, 2009;Kousha & Thelwall, 2017;Meyer, 2000aMeyer, , 2000bSarin et al, 2020;Tseng, Lin, & Lin, 2007;Venugopalan & Rai, 2015;Wang, Lei, & Lee, 2014;Ye, Huang, & Chen, 2016) sobre documentos de patente se limitaban al análisis de los datos bibliográficos (inventores, años, empresas, palabras clave, …), por ello, hasta la presente tesis, el estudio de los enlaces contenidos en patentes es muy limitado (Orduña-Malea, Thelwall, & Kousha, 2016).…”