Geographic clustering of research universities in specialized fields using Microsoft Academic Search

D. Kaczynski, Gongzhu Hu
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引用次数: 0

Abstract

Search is no doubt the most common activities on the Web. One of the most frequent search activities people in the educational and academic communities do is to search for research topics and papers and their author/affiliation information. For example, undergraduate students searching for graduate schools and master-level students searching for institutions for doctoral studies may go online to find universities that are conducting research in a highly specific field of their interest. A common way of doing this is to search journals and conferences for pertinent articles, and then accumulating the affiliations of the authors. In this paper, we present an interactive web-based academic search interface for discovering geographic clusters of academic institutions given a specific field by the user. The underlying system interacts with Microsoft Academic Search API and Google Places API, as well as Weka for clustering analysis. The system can be easily extended to accommodate other types of queries.
利用微软学术搜索对专业领域研究型大学的地理聚类
搜索无疑是网络上最常见的活动。在教育和学术团体中,人们做的最频繁的搜索活动之一是搜索研究主题和论文及其作者/隶属关系信息。例如,本科学生搜索研究生院,硕士学生搜索攻读博士学位的机构,他们可能会上网查找正在他们感兴趣的高度特定领域进行研究的大学。一种常见的方法是在期刊和会议上搜索相关的文章,然后累积作者的隶属关系。在本文中,我们提出了一个交互式的基于web的学术搜索界面,用于发现由用户给定特定领域的学术机构的地理集群。底层系统与Microsoft Academic Search API和谷歌Places API以及用于聚类分析的Weka交互。系统可以很容易地扩展,以适应其他类型的查询。
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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