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Reviewing academic social network mining applications

机译:审查学术社交网络挖掘应用程序

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摘要

Social network systems not only play important roles in peoples' social life but also help them in their professional life too. This study explores academic social network systems and particularly focuses on the data extraction methods to develop social relations. Several studies have used search engines to extract social networks from the Web and some systems get their data by description of their members' relation to others like Social Network Services or Friend-Of-A-Friend documents. Both types of data gathering have their own limitations such as data unreliability and scalability of queries to search engines. In this paper, a basic understanding of the issues in academic social network systems is provided. Different approaches to various problems of retrieving reliable data (relational information), as the major item of making these systems, are briefly described, and possible future research directions are discussed.
机译:社交网络系统不仅在人们的社会生活中发挥重要作用,而且在人们的职业生涯中也有帮助。这项研究探索了学术界的社交网络系统,尤其着重于发展社会关系的数据提取方法。一些研究使用搜索引擎从Web上提取社交网络,一些系统通过描述其成员与其他人的关系(例如,Social Network Services或“ Friend-of-A-Friend”文档)来获取数据。两种类型的数据收集都有其自身的局限性,例如数据不可靠和对搜索引擎的查询可伸缩性。在本文中,提供了对学术社交网络系统中问题的基本理解。作为制作这些系统的主要项目,简要描述了检索可靠数据(关系信息)的各种问题的不同方法,并讨论了可能的未来研究方向。

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