期刊全稱 | Advanced Methods for Knowledge Discovery from Complex Data | 影響因子2023 | Sanghamitra Bandyopadhyay,Ujjwal Maulik,Diane J. C | 視頻video | http://file.papertrans.cn/146/145934/145934.mp4 | 發(fā)行地址 | Covers a variety of advanced data mining techniques.Does not limit discussion to one specific domain area.First book to focus on advances on the synergy between application domains and algorithm types | 學(xué)科分類 | Advanced Information and Knowledge Processing | 圖書封面 |  | 影響因子 | The growth in the amount of data collected and generated has exploded in recent times with the widespread automation of various day-to-day activities, advances in high-level scienti?c and engineering research and the development of e?cient data collection tools. This has given rise to the need for automa- callyanalyzingthedatainordertoextractknowledgefromit,therebymaking the data potentially more useful. Knowledge discovery and data mining (KDD) is the process of identifying valid, novel, potentially useful and ultimately understandable patterns from massive data repositories. It is a multi-disciplinary topic, drawing from s- eral ?elds including expert systems, machine learning, intelligent databases, knowledge acquisition, case-based reasoning, pattern recognition and stat- tics. Many data mining systems have typically evolved around well-organized database systems (e.g., relational databases) containing relevant information. But, more and more, one ?nds relevant information hidden in unstructured text and in other complex forms. Mining in the domains of the world-wide web, bioinformatics, geoscienti?c data, and spatial and temporal applications comprise some illustrative example | Pindex | Book 2005 |
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