Scalable Link Prediction in Online Social Networks
نویسندگان
چکیده
We describe a link prediction method based on a scalable community detection algorithm. It can be used to recommend new links in a real world social network with millions of users. Using a Hadoop cluster, we test our implementation on a Twitter user network containing 40 million users and 1.4 billion connections. We show that communities detected can then be used to recommend new users to follow for existing users. We describe issues in evaluating a link recommendation algorithm. Finally we discuss the case of recommending influential users using a linear support vector machine classifier.
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تاریخ انتشار 2010