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：2017
卷号：5
期号：3
页码：5862
DOI：10.15680/IJIRCCE.2017.0503325
出版社：S&S Publications
摘要：In this era of post digitization organizations are generating, processing, and retaining data at a rate thatoften exceeds their ability to analyze it effectively; at the same time, the insights derived from these large data sets areoften key to the success of the organizations, allowing them to better understand how to solve hard problems and thusgain competitive advantage. Here we are trying to use publicly available machine learning algorithms to analyze usagepattern of a general storage element manager. To infer system insights from the log, we are using industry standardopen source elastic search to monitor and analyze user behavior. Using crowd sourcing as paradigm we are inferringuseful information, which is a feedback to the system, to improve multiple aspects like usability, traceability,supportability. Thus, the novelty of the approach is, it is purely open source based and it can be generalized for anykind of log analysis and prediction.
