Choi, Jaewoong Yoon, Janghyeok 2024-01-19T12:01:56Z 2024-01-19T12:01:56Z 2022-07-21 2022-05 1751-1577 https://pubs.kist.re.kr/handle/201004/115179 Although the incidence of knowledge exploration is observed in most patents, the concept of knowledge exploration distance has been analyzed with limited patents at the macro level of a company, organization or region. This study quantifies the knowledge exploration distance of individual patents using network embedding methods and citation analysis. First, a technology ecology network is constructed to identify technological association relationships between technical elements. Second, network embedding method is employed to represent technical elements as fixed dimensional vector, preserving the structural information. Next, the individual patents are vectorized based on the technology classification code information and pre-trained embedding values. Finally, by comparing the position between a citing patent and cited patents in the vector space, the knowledge exploration distance of the patent is obtained. This knowledge exploration distance indicates the novel degree of technological association between technical elements of a citing patent and those of cited patents. The case study covering artificial intelligence technology-related patents is conducted to illustrate the process of calculating knowledge exploration distance. Besides, this study showed that the proposed measure has significant relationships with patent-based indicators related to protection coverage, prior knowledge, and patent value. English Elsevier BV Measuring knowledge exploration distance at the patent level: Application of network embedding and citation analysis Article 10.1016/j.joi.2022.101286 1 Journal of Informetrics, v.16, no.2 Journal of Informetrics 16 2 N scie ssci scopus 000821684900006 Computer Science, Interdisciplinary Applications Information Science & Library Science Computer Science Information Science & Library Science Article TECHNOLOGY INNOVATION IDENTIFICATION EXPLOITATION FIRMS Knowledge exploration distance Patent citation Network embedding Patent classification code