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Techniques for comparing and recommending conferences
Journal of the Brazilian Computer Society Pub Date : 2017-03-14 , DOI: 10.1186/s13173-017-0053-z Grettel Monteagudo García , Bernardo Pereira Nunes , Giseli Rabello Lopes , Marco Antonio Casanova , Luiz André P. Paes Leme
Journal of the Brazilian Computer Society Pub Date : 2017-03-14 , DOI: 10.1186/s13173-017-0053-z Grettel Monteagudo García , Bernardo Pereira Nunes , Giseli Rabello Lopes , Marco Antonio Casanova , Luiz André P. Paes Leme
This article defines, implements, and evaluates techniques to automatically compare and recommend conferences. The techniques for comparing conferences use familiar similarity measures and a new measure based on co-authorship communities, called co-authorship network community similarity index. The experiments reported in the article indicate that the technique based on the new measure performs better than the other techniques for comparing conferences, which is therefore the first contribution of the article. Then, the article focuses on three families of techniques for conference recommendation. The first family adopts collaborative filtering based on the conference similarity measures investigated in the first part of the article. The second family includes two techniques based on the idea of finding, for a given author, the strongest related authors in the co-authorship network and recommending the conferences that his co-authors usually publish in. The first member of this family is based on the Weighted Semantic Connectivity Score—WSCS, which is accurate but quite costly to compute for large co-authorship networks. The second member of this family is based on a new score, called the Modified Weighted Semantic Connectivity Score—MWSCS, which is much faster to compute and as accurate as the WSCS. The third family includes the Cluster-WSCS-based and the Cluster-MWSCS-based conference recommendation techniques, which adopt conference clusters generated using a subgraph of the co-authorship network. The experiments indicate as the best performing conference recommendation technique the Cluster-WSCS-based technique. This is the second contribution of the article. Finally, the article includes experiments that use data extracted from the DBLP repository and a web-based application that enables users to interactively analyze and compare a set of conferences.
中文翻译:
比较和推荐会议的技巧
本文定义、实现和评估自动比较和推荐会议的技术。比较会议的技术使用熟悉的相似性度量和基于合着社区的新度量,称为合着网络社区相似度指数。文章中报告的实验表明,基于新度量的技术在比较会议方面的性能优于其他技术,因此这是本文的第一个贡献。然后,本文重点介绍了会议推荐的三类技术。第一个家族采用基于文章第一部分研究的会议相似性度量的协同过滤。第二个系列包括两种基于寻找给定作者的想法的技术,合着网络中最强的相关作者,并推荐他的合着者经常发表的会议。 这个家族的第一个成员是基于加权语义连接分数 - WSCS,它是准确的,但对于大的计算成本相当高合着网络。该系列的第二个成员基于一个新的分数,称为修改后的加权语义连接分数——MWSCS,它的计算速度要快得多,而且与 WSCS 一样准确。第三个家族包括基于集群 WSCS 和基于集群 MWSCS 的会议推荐技术,它们采用使用共同作者网络的子图生成的会议集群。实验表明,基于集群 WSCS 的技术是性能最佳的会议推荐技术。这是文章的第二个贡献。
更新日期:2017-03-14
中文翻译:
比较和推荐会议的技巧
本文定义、实现和评估自动比较和推荐会议的技术。比较会议的技术使用熟悉的相似性度量和基于合着社区的新度量,称为合着网络社区相似度指数。文章中报告的实验表明,基于新度量的技术在比较会议方面的性能优于其他技术,因此这是本文的第一个贡献。然后,本文重点介绍了会议推荐的三类技术。第一个家族采用基于文章第一部分研究的会议相似性度量的协同过滤。第二个系列包括两种基于寻找给定作者的想法的技术,合着网络中最强的相关作者,并推荐他的合着者经常发表的会议。 这个家族的第一个成员是基于加权语义连接分数 - WSCS,它是准确的,但对于大的计算成本相当高合着网络。该系列的第二个成员基于一个新的分数,称为修改后的加权语义连接分数——MWSCS,它的计算速度要快得多,而且与 WSCS 一样准确。第三个家族包括基于集群 WSCS 和基于集群 MWSCS 的会议推荐技术,它们采用使用共同作者网络的子图生成的会议集群。实验表明,基于集群 WSCS 的技术是性能最佳的会议推荐技术。这是文章的第二个贡献。