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.
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... financial transactions, recognising threats to ecological systems, etc. In such applications, data mining is only part of the total process. Experts and clients are needed in most stages of the project: to define and redefine the ...
A methodology that covers the process from problem definition to presentation and delivery of the resulting patterns was developed in the CRISPDM project (Chapman, et al., 2000) and is becoming a de facto industrial standard.
More specifically, data mining is concerned with finding patterns and/or models in data which are interesting and valid (according to some user defined measures of interestingness and validity, respectively).
... which do not need to be defined in advance. However, the typical operations on data warehouses were similar to the ones from the traditional OLTP databases in that the user issued a query and received a data table as a result.
While a typical operation in OLTP affects only in the order of ten records in pre-defined scenarios, a typical operation in OLAP affects up to millions of records (sometimes all records) in the database in a non-predefined way.
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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