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Parallel Implementation of Fuzzy Clustering Algorithm Based on MapReduce Computing Model of Hadoop – A Detailed Survey
| Content Provider | Semantic Scholar |
|---|---|
| Author | Mathew, Jerril Mathson Chandran, Lekshmy P. |
| Copyright Year | 2015 |
| Abstract | Clustering is regarded as one of the significant task in data mining which deals with primarily grouping of similar data. To cluster large data is a point of apprehension. Hadoop is a software framework which deals with distributed processing of huge amount of data across clusters of distributed computers using MapReduce programming model. MapReduce allows a kind of parallelization to solve a problem that involves large datasets using computing clusters and is also a striking implication for data clustering involving large datasets. Mahout, a scalable machine learning library is an approach to Fuzzy clustering which runs on Hadoop. This paper focuses on studying the performance of using Fuzzy K-mean clustering in MapReduce on Hadoop. KeywordsFuzzy C Means Clustering (FCM), MapReduce, Hadoop, HDFS, Mahout, Parallel Computing. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://ijcsit.com/docs/Volume%206/vol6issue05/ijcsit20150605124.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
