Exploring Evolutionary Technical Trends from Academic Research Papers

Teng Kai Fan, Chia Hui Chang

研究成果: 雜誌貢獻期刊論文同行評審

1 引文 斯高帕斯(Scopus)

摘要

Technical terms are vital elements for understanding the techniques used in academic research papers, and in this paper, we use focused technical terms to explore technical trends in the research literature. The major purpose of this work is to understand the relationship between techniques and research topics to better explore technical trends. We define this new text mining issue and apply machine learning algorithms for solving this problem by (1) recognizing focused technical terms from research papers; (2) classifying these terms into predefined technology categories; (3) analyzing the evolution of technical trends. The dataset consists of 656 papers collected from well-known conferences on ACM. The experimental results indicate that our proposed methods can effectively explore interesting evolutionary technical trends in various research topics.

原文???core.languages.en_GB???
頁(從 - 到)97-117
頁數21
期刊Journal of Information Science and Engineering
26
發行號1
出版狀態已出版 - 1月 2010

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