Improving similarity measures of relatedness proximity: Toward augmented concept maps
作者：
Highlights：
• An augmented concept mapping model based on co-occurrence analysis and information extraction is proposed.
• A novel method of co-word analysis that utilizes webometrics for improving similarity measure of relatedness proximity.
• An automated research instrument that collects a corpus of texts on the web for a spectrum of IT is demonstrated and validated.
• A tool capable of presenting a solid and precise picture of a specific knowledge domain in terms of an augmented concept map.
• The model contribution is emphasized by the current growing attention to the big data phenomenon.
摘要
•An augmented concept mapping model based on co-occurrence analysis and information extraction is proposed.•A novel method of co-word analysis that utilizes webometrics for improving similarity measure of relatedness proximity.•An automated research instrument that collects a corpus of texts on the web for a spectrum of IT is demonstrated and validated.•A tool capable of presenting a solid and precise picture of a specific knowledge domain in terms of an augmented concept map.•The model contribution is emphasized by the current growing attention to the big data phenomenon.
论文关键词：Augmented concept map,Relatedness proximity,Co-word analysis,Webometrics,Technology assessment
论文评审过程：Received 18 December 2014, Revised 16 June 2015, Accepted 17 June 2015, Available online 9 July 2015, Version of Record 9 July 2015.
论文官网地址：https://doi.org/10.1016/j.joi.2015.06.003
