A Novel Evolutionary Biclustering Approach using MapReduce(EBC-MR)
| Autor: | R. Rathipriya |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Measure (data warehouse)
Computer science 020206 networking & telecommunications 02 engineering and technology computer.software_genre Correlation value Local pattern Local convergence Set (abstract data type) Biclustering ComputingMethodologies_PATTERNRECOGNITION Genetic algorithm 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Web usage data Data mining computer |
| Zdroj: | International Journal of Knowledge Discovery in Bioinformatics. 6:26-36 |
| ISSN: | 1947-9123 1947-9115 |
| DOI: | 10.4018/ijkdb.2016010103 |
| Popis: | A novel biclustering approach is proposed in this paper, which can be used to cluster data (like web data, gene expression data) into local pattern using MapReduce framework. The proposed biclustering approach extracts the highly coherent bicluster using a correlation measure called Average Correlation Value measure. Furthermore, MapReduce based genetic algorithm is firstly used to the biclustering of web data. This method can avoid local convergence in the optimization algorithms mostly. The MSWeb dataset and MSNBC web usage data set are used to test the performance of new MapReduce based Evolutionary biclustering algorithm. The experimental study is carried out for comparison of proposed algorithm with traditional genetic algorithm in biclustering. The results reveal that novel proposed approach preforms better than existing evolutionary biclustering approach. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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