Text and Dynamic Network Analysis for Measuring Technological Convergence: A Case Study on Defense Patent Data

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3A9ELSJ4SH" target="_blank" >RIV/00216208:11320/23:9ELSJ4SH - isvavai.cz</a>

Výsledek na webu

<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85107354845&doi=10.1109%2fTEM.2021.3078231&partnerID=40&md5=2d5e43efa12c7f7b2cff7be8bab260f9" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85107354845&doi=10.1109%2fTEM.2021.3078231&partnerID=40&md5=2d5e43efa12c7f7b2cff7be8bab260f9</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/tem.2021.3078231" target="_blank" >10.1109/tem.2021.3078231</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Text and Dynamic Network Analysis for Measuring Technological Convergence: A Case Study on Defense Patent Data

Popis výsledku v původním jazyce

"Identifying technology convergence is getting harder, especially in fast-evolving and cross-technological fields. On the other side, natural language processing and network analysis researchers is to provide a novel method for mapping technologies and their relations over time, in order to identify dynamic patterns of convergence and to test it on the C4ISTAR field, a defense-related cross-technological field. The methodology automatically extracts technologies from a corpus of scientific papers, policy documents, websites, and company reports using Named Entity Recognition approaches. These technologies are then retrieved from the second corpus of more than 300 thousand patents related to the C4ISTAR domain, measuring their cooccurrences over time. Finally, using the time-varying network analysis, we were able to identify and measure the pattern of technological convergence. © 1988-2012 IEEE."

Název v anglickém jazyce

Text and Dynamic Network Analysis for Measuring Technological Convergence: A Case Study on Defense Patent Data

Popis výsledku anglicky

"Identifying technology convergence is getting harder, especially in fast-evolving and cross-technological fields. On the other side, natural language processing and network analysis researchers is to provide a novel method for mapping technologies and their relations over time, in order to identify dynamic patterns of convergence and to test it on the C4ISTAR field, a defense-related cross-technological field. The methodology automatically extracts technologies from a corpus of scientific papers, policy documents, websites, and company reports using Named Entity Recognition approaches. These technologies are then retrieved from the second corpus of more than 300 thousand patents related to the C4ISTAR domain, measuring their cooccurrences over time. Finally, using the time-varying network analysis, we were able to identify and measure the pattern of technological convergence. © 1988-2012 IEEE."

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

—

Rok uplatnění

2023

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

"IEEE Transactions on Engineering Management"

ISSN

0018-9391

e-ISSN

—

Svazek periodika

70

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

14

Strana od-do

1490-1503

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-85107354845