Data Mining and Decision Support: Integration and Collaboration
Dunja Mladenic, Nada Lavrač, Marko Bohanec, Steve Moyle
Springer Science & Business Media, Dec 6, 2012 - Computers - 275 pages
Data mining deals with finding patterns in data that are by user-definition, interesting and valid. It is an interdisciplinary area involving databases, machine learning, pattern recognition, statistics, visualization and others.
Independently, data mining and decision support are well-developed research areas, but until now there has been no systematic attempt to integrate them. Data Mining and Decision Support: Integration and Collaboration, written by leading researchers in the field, presents a conceptual framework, plus the methods and tools for integrating the two disciplines and for applying this technology to business problems in a collaborative setting.
The first two chapters cover data mining and the specific area of text and web mining. The next two chapters describe decision support itself and the proposed technology for data mining and decision support integration.
However, the book allows also for selective reading of specific areas in the manner which follows. A reader interested in data mining only is suggested to read Chapters 1 and 2 of Part I and followed by reading about the real-life ...
The US project on Evidence Extraction and Link Discovery addresses similar issues but in the context of specific applications such as military decision making and discovering terrorist ...
In addition to the CRISP-DM standardized methodology for building data mining applications, standards covering specific phases of the process are also emerging. These standards include: — the XML-based Predictive Modeling Markup ...
For the future we envisage intensive developments in specific domain areas (e.g., bioinformatics, multimedia data, textual and web data) in collaboration with clients and researchers from different application areas.
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TEXT AND WEB MINING
INTEGRATION OF DATA MINING AND DECISION
COLLABORATION IN A DATA MINING VIRTUAL
DATA MINING PROCESSES AND COLLABORATION
MINING 21 YEARS OF
ANALYSIS OF A DATABASE OF RESEARCH PROJECTS
WEBSITE ACCESS ANALYSIS FOR A NATIONAL
FIVE DECISION SUPPORT APPLICATIONS
COLLABORATIVE DATA MINING WITH RAMSYS
LESSONS LEARNED FROM DATA MINING DECISION
ACADEMIABUSINESS PARTNERSHIP MODELS
PREPROCESSING FOR DATA MINING AND DECISION
DATA MINING AND DECISION SUPPORT INTEGRATION
APPLICATIONS OF DATA MINING
Subject index 271