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Web Mining for Identifying Research Trends

机译:Web挖掘以识别研究趋势

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摘要

This paper proposes a web mining approach for identifying research trends. The proposed approach comprises a number of data mining techniques. To perform web mining, the Indexing Agents search and download scientific publications from web sites that typically include academic web pages, then they extract citations and store them in a Web Citation Database. The Temporal Document Clustering technique and Journal Co-Citation Clustering technique are applied to the Web Citation Database to generate temporal document clusters and journal clusters respectively. The Multi-Clustering technique is then proposed to mine the document and journal clusters for their interrelationships. Finally, the knowledge that is mined from the inter-relationships is used for the detection of trends and emergent trends for a specified research area. In this paper, we will discuss the proposed web mining approach, and the performance of the proposed approach.
机译:本文提出了一种用于确定研究趋势的网络挖掘方法。所提出的方法包括许多数据挖掘技术。为了执行Web挖掘,索引代理从通常包括学术网页的网站中搜索和下载科学出版物,然后提取引文并将其存储在Web引文数据库中。将时间文档聚类技术和期刊共引聚类技术应用于Web Citation数据库,以分别生成时间文档聚类和期刊聚类。然后提出了多聚类技术,以挖掘文档和日记帐群集之间的相互关系。最后,从相互关系中获得的知识用于检测特定研究领域的趋势和新兴趋势。在本文中,我们将讨论提出的Web挖掘方法以及提出的方法的性能。

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