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  • 标题:Swarm Search Using Wordnet and Hadoop
  • 本地全文:下载
  • 作者:Avinash Palave ; Archana Thakur ; Priyanka Ranpise
  • 期刊名称:International Journal of Innovative Research in Computer and Communication Engineering
  • 印刷版ISSN:2320-9798
  • 电子版ISSN:2320-9801
  • 出版年度:2016
  • 卷号:4
  • 期号:3
  • 页码:3363
  • DOI:10.15680/IJIRCCE.2016.0403074
  • 出版社:S&S Publications
  • 摘要:Now a days handing of big data is not easy because its size and complexity .The capability of removing or take out useful information from these large datasets of data, because of its volume, variability, and velocity is nothing but the big data , it was impossible earlier to do it. PSO is a naturally distributed algorithm Particle Swarm Optimizers are naturally dist ributed algorithms in that solution to problem is form by interaction between different particles. T his is concept related to Data mining. It includes, Particle Swarm Data Mining Algorithms in which we implemented and tested across a natural Algorithm and a Decision Tree Algorithm . From the archived results, Particle Swarm Optimizers proven that it is to be a sufficient for classification tasks. The data which used for experimental testing are commonly existing standard for rule discovery algorithms re liability ranking .Also the feature selection algorithm used to remove a redundancy in document and gives most relevant document .W ordnet provide you different synonyms for search the given word in hadoop document
  • 关键词:Particle swarm optimizationalgorithm; Feature selection; Hadoop;Mining Big data stream; Decision tree
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