图书章节

Missing Link Prediction in Social Networks 收藏

社交网络中缺失链接预测

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作者

Jin Zhou1;Chiman Kwan1

作者单位

1.Signal Processing, Inc.RockvilleUSA

关键词

Link prediction and recovery ;Social networks ;Recommender system ;Github

关键词译文

链接预测和恢复;社交网络;推荐系统; Github

发布日期

26 May 2018

页码

346-354

DOI

10.1007/978-3-319-92537-0_40

来源信息

Advances in Neural Networks – ISNN 2018 ISBN：9783319925363, 2018年, 346-354页

摘要

This paper summarizes our effort of applying matrix completion techniques to a popular social network problem: link prediction. The results of our matrix completion algorithm are comparable or even better than the results of state-of-the-art methods. This means that matrix completion is a promising technique for social network problems. In addition, we customize our algorithm and developed a recommender system for Github. The recommender can help users find software tools that match their interest.

摘要译文

本文总结了我们将矩阵完成技术应用于流行的社交网络问题的努力：链接预测。我们的矩阵完成算法的结果与现有技术方法的结果相当甚至更好。这意味着矩阵完成是一种有前途的社交网络问题技术。此外，我们定制我们的算法并为Github开发了一个推荐系统。推荐人可以帮助用户找到符合他们兴趣的软件工具。

Jin Zhou1;Chiman Kwan1. Missing Link Prediction in Social Networks. Advances in Neural Networks – ISNN 2018[M].DE: Springer;LNCS, 2018: 346-354