文章摘要
阮剑,杨海霞,黄瑱.基于主题模型的大学学报文献挖掘研究——以计算机科学领域为例[J].情报工程,2017,3(4):039-047
基于主题模型的大学学报文献挖掘研究——以计算机科学领域为例
Research on Document Mining of University Journals Based on Topic Model——An Example of Computer Science
  
DOI:10.3772/j.issn.2095-915X.2017.04.006
中文关键词: 大学学报,计算机科学,主题模型,主题分析,趋势分析
英文关键词: University journal, computer science, topic model, topic evaluation, trend analysis
基金项目:
作者单位
阮剑 武汉大学信息管理学院;武汉大学自然科学学报编辑部 
杨海霞 武汉大学经济与管理学院 
黄瑱 武汉大学自然科学学报编辑部 
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中文摘要:
      大数据时代下,运用文本挖掘技术自动从海量科技文献中提取研究主题并探测研究趋势十分重要。基于LDA 主题模型,考虑科技文献的发表时间信息,对优秀“综合性科学技术”类大学学报2006-2014 期间刊载的计算机科学类文献进行主题内容和主题强度分析;同时基于计算机专业期刊文献,进行研究趋势探测。本文从25 个研究主题中得到7 个强度增强的研究主题和6 个强度减弱的研究主题,揭示大学学报文献中我国高等院校对计算机科学领域的研究状态。通过对数据进行挖掘和分析,了解我国高等院校在计算机科学研究领域的研究趋势,帮助从事该领域研究的学者寻找新兴研究主题,有助于大学学报在定向组稿和学术专辑出版中,把握学术热点与前沿方向,进而提高学报的影响力。
英文摘要:
      In the era of big data, it is very important to use text mining technology to automatically extract research topics from large amounts of scientific and technological literature for detecting the research trends. Considering the publication time information of scientific and technical literature, this study analyzed the topic content and topic intensity of computer science journals based on the latent dirichlet allocation (LDA) model from the catalog of “comprehensive science and technology” during the period of 2006-2014. Meanwhile, this research also studied the research trends based on the professional literatures of computer journal. This study obtained seven enhanced research topic and six weakened topic from total 25 topics, which indicated the research status of computer science in the colleges and universities of China. Through the data mining and analysis, this research revealed the development of computer science in the colleges and universities of China, which may assistant the researchers in this field to find out the new research topic, and it is also helpful to the university journal for grasping academic hot spot and front direction soliciting contributions and academic album publishing for improving the influence of the university journal.
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