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Titlebook: Computational Intelligence in Data Mining - Volume 2; Proceedings of the I Lakhmi C. Jain,Himansu Sekhar Behera,Durga Prasad Conference pr

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發(fā)表于 2025-3-21 16:37:35 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱Computational Intelligence in Data Mining - Volume 2
副標(biāo)題Proceedings of the I
編輯Lakhmi C. Jain,Himansu Sekhar Behera,Durga Prasad
視頻videohttp://file.papertrans.cn/233/232482/232482.mp4
概述Presents latest research findings in data mining.Entails thought-provoking developments to help research students.Discusses most recent cutting edge scientific technologies in computing.Includes suppl
叢書(shū)名稱Smart Innovation, Systems and Technologies
圖書(shū)封面Titlebook: Computational Intelligence in Data Mining - Volume 2; Proceedings of the I Lakhmi C. Jain,Himansu Sekhar Behera,Durga Prasad Conference pr
描述The contributed volume aims to explicate and address the difficulties and challenges that of seamless integration of the two core disciplines of computer science, i.e., computational intelligence and data mining. Data Mining aims at the automatic discovery of underlying non-trivial knowledge from datasets by applying intelligent analysis techniques. The interest in this research area has experienced a considerable growth in the last years due to two key factors: (a) knowledge hidden in organizations’ databases can be exploited to improve strategic and managerial decision-making; (b) the large volume of data managed by organizations makes it impossible to carry out a manual analysis. The book addresses different methods and techniques of integration for enhancing the overall goal of data mining. The book helps to disseminate the knowledge about some innovative, active research directions in the field of data mining, machine and computational intelligence, along with some current issues and applications of related topics.
出版日期Conference proceedings 2015
關(guān)鍵詞Advance Computing Methods; Big Data Analysis; CIDM; CIDM 2014; CIDM 2014 Proceedings; CIDM Proceedings; Co
版次1
doihttps://doi.org/10.1007/978-81-322-2208-8
isbn_softcover978-81-322-3561-3
isbn_ebook978-81-322-2208-8Series ISSN 2190-3018 Series E-ISSN 2190-3026
issn_series 2190-3018
copyrightSpringer India 2015
The information of publication is updating

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Strategic Analysis: Strategy Modeling, of metrics for measuring the understand ability of conceptual data model for data warehouses. The statistical and machine learning methods are used to predict effect of structural metrics, on understand ability, efficiency and effectiveness of Data warehouse Multidimensional (MD) conceptual model.
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Strategic Planning for The Family Businesshas a strong global search capability is used for dimensionality optimization. Weighted aggregation method is employed as multi-objective functions. The proposed system has the high intrusion detection accuracy of 97.54?% with a detection time is 0.20?s.
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Quality Assessment of Data Using Statistical and Machine Learning Methods, of metrics for measuring the understand ability of conceptual data model for data warehouses. The statistical and machine learning methods are used to predict effect of structural metrics, on understand ability, efficiency and effectiveness of Data warehouse Multidimensional (MD) conceptual model.
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