Community Detection Algorithms for Big Data using Graph Theory
Ram Milan1, Diwakar Shukla2, Kamlesh Kumar Pandey3

1Mr. Ram Milan, Department of Computer Science and Applications, Dr. Harisiingh Gour Vishwavidyalaya, Sagar (M.P), India.
2Prof. Diwakar Shukla, Department of Computer Science and Applications, Dr. Harisiingh Gour Vishwavidyalaya, Sagar (M.P), India.
3Mr. Kamlesh Kumar Pandey, Department of Computer Science and Applications, Dr. Harisiingh Gour Vishwavidyalaya, Sagar (M.P), India.
Manuscript received on 18 September 2019 | Revised Manuscript received on 05 October 2019 | Manuscript Published on 11 October 2019 | PP: 273-280 | Volume-8 Issue-2S10 September 2019 | Retrieval Number: B10460982S1019/2019©BEIESP | DOI: 10.35940/ijrte.B1046.0982S1019
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Community detection is a nowadays research problem in the Big Data era related to huge volume, variety, and velocity of data. Big data defines data where normal processing, storage, retrieval fails and require some advanced tools to solve these types of problem. An important tool in the analysis of complex network is community detection. Community detection or community mining is a technique which is used to find the same type of relations in a particular group. Community detection is also known as Graph Clustering. This paper represents Big data in the form of graphs and detects community via some graph algorithms like METIS, Spectral Partitioning, hierarchical clustering, Markov Clustering, Genetic Algorithm based community detection algorithm, etc. Community detection is widely used in various types of disease detection, drug formation, species clustering. It can be also used in social networking sites to control crimes by detecting community bad peoples.
Keywords: Community Detection, Big Data, Graph Clustering, Markov Clustering.
Scope of the Article: Big Data Quality Validation