The small-world phenomenon: an algorithmic perspective
STOC '00 Proceedings of the thirty-second annual ACM symposium on Theory of computing
Web Intelligence
Discovering global network communities based on local centralities
ACM Transactions on the Web (TWEB)
An Operable Email Based Intelligent Personal Assistant
World Wide Web
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Although they have small-world and searchable characteristics, social networks always protect local structure which makes local search very hard. Social networks not only have power-law distribution, but also have higher connectivity or clustering characteristics. Meanwhile, several social networks are weighted and directed. Hence we should utilize these extra information. In this paper, we propose and theoretically analyze local search strategies such as SS, O1, O2, SPD and LPD which consider weights, single link characteristics and direction information. We finally demonstrate the results of these strategies on Enron Email networks. Experimental results show that weighted and directed information is able to enhance the efficiency of local search.