Trend Analysis of Machine Learning - A Text Mining And Document Clustering Methodology

Jiann-Min Yang, Wei-Cheng Liao, Wen-Chin Wu, Chi-Yen Yin
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引用次数: 2

Abstract

The Machine Learning is certificated as one of the most important technologies in today’s world. There are several various researches applying Machine Learning to improve its operation efficiency in many different aspects.Based on the Social Science Citation Index (SSCI) database,this research is using text mining technology which collecting the homogeneous glossaries in the articles, conducting to the literature cluster analysis. To select the term frequency index which generated by various glossaries aggregation from each article as well as an input variable for Self-Organization map(SOM) network, following by utilizing the network neuron automatic clustering function, dividing into 10 application domains of machine learning, finally proceeding the trend analysis coordinated with the articles by published year,discovering the historical vein and collecting the results by each research area, and further forecasting the future possible tendency.
机器学习的趋势分析-一种文本挖掘和文档聚类方法
机器学习被公认为当今世界最重要的技术之一。应用机器学习来提高其运行效率的研究有很多。本研究基于社会科学引文索引(SSCI)数据库,采用文本挖掘技术收集文章中的同构词汇,对文献进行聚类分析。从每篇文章中选取各种词汇聚合产生的词频指数和自组织地图(SOM)网络的输入变量,然后利用网络神经元自动聚类函数,将机器学习划分为10个应用领域,最后按发表年份与文章进行趋势分析,发现历史脉络并收集各个研究领域的结果。并进一步预测未来的可能趋势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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