项目名称: 网络环境下科研新趋势的识别与实时追踪研究
项目编号: No.61301227
项目类型: 青年科学基金项目
立项/批准年度: 2014
项目学科: 无线电电子学、电信技术
项目作者: 王贤文
作者单位: 大连理工大学
项目金额: 24万元
中文摘要: 以往的研究趋势分析都是通过对已发表文献进行回溯研究,较长的时间滞后周期使得分析的结果往往已是过去的研究趋势。本研究提出一种新的思路:科研工作者如果在思考某一问题,就会从科学文献数据库中搜索和下载相关文献;因而,通过获取研究者正在下载的科学文献信息,则可以反过来判断科学家目前正在从事的研究主题。基于这一思路,本课题提出追踪科学研究趋势的一种新方法:基于网络信息获取科学文献的即时使用信息,实时追踪某一领域的研究趋势、挖掘研究热点、探测研究前沿。课题提出网络环境下从数据到信息、再到知识和智慧的科研新趋势挖掘DIKW模型。基于该模型,以计算神经学为例,构建该领域科研新趋势的知识挖掘系统。通过对该领域论文进行7*24小时不间断的长期监测,收集该领域论文的实时被下载数据,辅以文献在社交媒体中的标记和讨论信息,应用文本挖掘、信息计量学方法实现对研究热点和研究新动向的挖掘。
中文关键词: 研究热点;使用数据;科学计量学;计算神经科学;altmetrics
英文摘要: Former studies on research trends are based on published articles. Those results inevitably turn out to reveal past trends due to the publication time lag. This study, however, provides a new idea to investigate research trends. As is known to all, when scientists are considering some research topics or conducting advanced research, they tend to search and download related publications in scientific databases. Accordingly, the downloaded publications, if explored properly, would largely reflect the subjects scientists are working on. So we propose a new method. Based on the timely usage data of the web-based tools, we intend to track the research trends, delve into the hot topics, and explore the emerging research fronts in certain scientific fields. We design a trends tracing DIKW model, which is composed of Data, Information, Knowledge, and Wisdom. Specifically, we probe into neurocomputing, and establish a knowledge mining system. By monitoring the article downloads 24/7, we collect the realtime downloads data and other social-web-based usage data. In this study, data mining and informetrics methods are applied to analyze the latest research trends.
英文关键词: hot topic;usage data;Scientometrics;neurocomputing;altmetrics