eprintid: 3851
rev_number: 6
eprint_status: archive
userid: 69
dir: disk0/00/00/38/51
datestamp: 2017-12-28 11:03:30
lastmod: 2017-12-28 11:03:30
status_changed: 2017-12-28 11:03:30
type: book_section
metadata_visibility: show
creators_name: Gao, Yuan
creators_name: Zhu, Zhen
creators_name: Riccaboni, Massimo
creators_id: 
creators_id: 
creators_id: massimo.riccaboni@imtlucca.it
title: Consistency and Trends of Technological Innovations: A Network Approach to the International Patent Classification Data
ispublished: pub
subjects: HA
subjects: HD
divisions: CSA
full_text_status: none
abstract: Classifying patents by the technology areas they pertain is important to enable information search and facilitate policy analysis and socio-economic studies. Based on the OECD Triadic Patent Family database, this study constructs a cohort network based on the grouping of IPC subclasses in the same patent families, and a citation network based on citations between subclasses of patent families citing each other. This paper presents a systematic analysis approach which obtains naturally formed network clusters identified using a Lumped Markov Chain method, extracts community keys traceable over time, and investigates two important community characteristics: consistency and changing trends. The results are verified against several other methods, including a recent research measuring patent text similarity. The proposed method contributes to the literature a network-based approach to study the endogenous community properties of an exogenously devised classification system. The application of this method may improve accuracy and efficiency of the IPC search platform and help detect the emergence of new technologies.
date: 2018
date_type: published
series: Studies in Computational Intelligence
volume: 689
publisher: Springer International Publishing
pagerange: 744-756
id_number: DOI: 10.1007/978-3-319-72150-7_60
refereed: TRUE
isbn: 978-3-319-72150-7
book_title: Complex Networks & Their Applications VI. COMPLEX NETWORKS 2016 2017. Studies in Computational Intelligence
official_url: https://doi.org/10.1007/978-3-319-72150-7_60
citation:   Gao, Yuan and Zhu, Zhen and Riccaboni, Massimo  Consistency and Trends of Technological Innovations: A Network Approach to the International Patent Classification Data.   In:  Complex Networks & Their Applications VI. COMPLEX NETWORKS 2016 2017. Studies in Computational Intelligence.   Studies in Computational Intelligence, 689 .  Springer International Publishing, pp. 744-756.  ISBN 978-3-319-72150-7      (2018)