Data warehousing and mining: concepts, methodologies, tools, and applications, Volume 2
In recent years, the science of managing and analyzing large datasets has emerged as a critical area of research. In the race to answer vital questions and make knowledgeable decisions, impressive amounts of data are now being generated at a rapid pace, increasing the opportunities and challenges associated with the ability to effectively analyze this data. Data Warehousing and Mining: Concepts, Methodologies, Tools and Applications provides the most comprehensive compilation of research available in this emerging and increasingly important field. This six-volume set offers tools, designs, and outcomes of the utilization of data mining and warehousing technologies, such as algorithms, concept lattices, multidimensional data, and online analytical processing. With more than 300 chapters contributed by over 575 experts from around the globe, this authoritative collection will provide libraries with the essential reference on data mining and warehousing.
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28 Best Practices in Data Warehousing from the Federal
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aggregation algorithm analysis applications approach association rules attributes cache Chapter classifiers clustering co-clustering component computed concept data cubes data mining data model data set data streams data warehouse Data Warehousing database decision tree defined deployment diagrams developed dimension distance domain DSCL engine evaluation example fact table Figure function fuzzy genetic algorithm geographical Grid service identify implementation input instance integration International Conference knowledge discovery machine learning Management mapping ment method metric mining and warehousing mobile agent multidimensional nodes non-spatial objects OLAP ontology operators parameters partition patterns performance problem Proceedings proposed protein query registrations represented Retrieved schema score selection semantic sequence server service discovery solution spatial data spatial measure specific speedup star schema stored structure tablespaces techniques Technology tion transaction University update values workflow WSML