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The Big data analytics gives new chances to the enterprises to enhance their management and manufacturing levels. A solution with case study is proposed to accomplish deep-level quality management based on big data analytics. First, the implementation of big data analytics based on industrial process data is illustrated with case study illustration. Through the analysis and feature extraction of off-line...
Expectation-Maximization (EM) is typically used to compute maximum likelihood estimates given incomplete samples and estimated the parameters. We proposed a new algorithm for generating an extension Dynamic Topic Model (exDTM)-in a time-based manner and based on the distribution of documents topics on Spark. The proposed algorithm can be applied in clustering documents from data streams for threat...
Big data is a big business, and effective modeling of this data is key. This paper provides a comprehensive multidimensional analysis of various open source tools for machine learning with big data. An evaluation standard is proposed along with detailed comparisons of the frameworks discussed, with regard to algorithm availability, scalability, speed, and more. The major tools profiled are Mahout,...
Big Data analytics are recently coming up as prominent research area in the field of Information Technology serving various data driven domains for effective processing of big data. Big data analytics have been facing various challenges such as inefficient storage, processing delays, low rate of information retrieval, complex algorithms which cannot be handled and managed using traditional methods...
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