NDLI: A MapReduce and Information Compression Based Social Community Structure Mining Method

Content Provider	IEEE Xplore Digital Library
Author	Jin Songchang Li Aiping Yang Shuqiang Lin Wangqun Deng Bo Li Shudong
Copyright Year	2013
Description	Author affiliation: Coll. of Math. & Inf. Sci., Shandong Inst. of Bus. & Technol., Yantai, China (Li Shudong) \|\| Sch. of Comput., Nat. Univ. of Defense Technol., Changsha, China (Jin Songchang; Li Aiping; Yang Shuqiang) \|\| Beijing Inst. of Syst. & Eng., Beijing, China (Lin Wangqun; Deng Bo)
Abstract	As the rapid development of social media, social community structure mining has become a popular research field in recent years. But traditional social community mining methods are not able to effectively deal with the data of large scale networks. We firstly introduce an information compression based community mining model in this paper, and with the help of the model, we transform the community mining problem into optimal information coding problem. And then propose a parallel computing method CInfoMR based on the MapReduce parallel framework to mine the social community structure. In the InfoMR, map tasks are responsible for splitting network data into a plenty of subsets, each reduce task is responsible for accomplishing community clustering by means of loop iteration on its subset, and finally all the results from the reduce phase are merged together to output. Theoretical analysis and related experiments verify the validity of the work in this paper. The results of the accuracy experiments show that, the accuracy of the InfoMR is much higher than that of Fast GN and PDST algorithm. The performance experiments on 2 real dataset and 2 simulative dataset show that InfoMR is able to accomplish the task of mining social community in a relatively short period of time on big data social networks.
Starting Page	971
Ending Page	980
File Size	456070
Page Count	10
File Format	PDF
ISBN	9780769550961
DOI	10.1109/CSE.2013.143
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-12-03
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	social network information compression random walk Social network services Data handling Communities Information management social community Channel coding Data storage systems MapReduce
Content Type	Text
Resource Type	Article

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