文章基本信息

标题：Improving the Performance of Information Collection Using Social Networks with Online Sampling
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作者：Praveen Kumar Ramtekkar ; Shyam P. Dubey ; Mohammad Shahid Nadeem 等
期刊名称：International Journal of Engineering and Computer Science
印刷版ISSN：2319-7242
出版年度：2016
卷号：5
期号：9
页码：18025-18028
DOI：10.18535/ijecs/v5i9.40
出版社：IJECS
摘要：This paper concentrates on improving the performance of information collection from the neighborhood of a user in a dynamic social network. By introducing sampling based algorithms to efficiently explore a user’s social network respecting its structure and to quickly approximate quantities of interest. It introduces and analyzes variants of the basic sampling scheme exploring correlations across the samples. As online social networking emerges, there has been increased interest to utilize the underlying network structure as well as the available information on social peers to improve the information needs of a user. Models of centralized and distributed social networks are considered to implement this algorithm.This algorithm can be utilized to grade items in the neighborhood of a user, assuming that information for each user in the network is available. Using real and synthetic data sets, this work validates the results of analysis and expresses the efficiency of algorithms in approximating quantities of interest. The methods described are general and can probably be easily adopted in a variety of strategies aiming to efficiently collect information from a social graph
关键词：social network; facebook; twitter; online social network; depth first search