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Data Warehousing and Knowledge Discovery
Il Yeol SongJohann EderTho Manh Nguyen
其他書名
9th International Conference, DaWaK 2007, Regensburg, Germany, September 3-7, 2007, Proceedings
出版Springer Science & Business Media, 2007-08-21
主題Business & Economics / Information ManagementComputers / GeneralComputers / Artificial Intelligence / GeneralComputers / Business & Productivity Software / GeneralComputers / Database Administration & ManagementComputers / Data Science / Data AnalyticsComputers / Data Science / Data WarehousingComputers / Artificial Intelligence / Expert SystemsComputers / System Administration / Storage & RetrievalComputers / Information TheoryComputers / Information TechnologyComputers / Management Information SystemsComputers / Networking / GeneralComputers / Programming / AlgorithmsComputers / Networking / HardwareLanguage Arts & Disciplines / Library & Information Science / GeneralMathematics / Probability & Statistics / General
ISBN35407455219783540745525
URLhttp://books.google.com.hk/books?id=oBCj5q8pxVoC&hl=&source=gbs_api
EBookSAMPLE
註釋Data Warehousing and Knowledge Discovery have been widely accepted as key te- nologies for enterprises and organizations to improve their abilities in data analysis, decision support, and the automatic extraction of knowledge from data. With the exponentially growing amount of information to be included in the decision-making process, the data to be processed become more and more complex in both structure and semantics. Consequently, the process of retrieval and knowledge discovery from this huge amount of heterogeneous complex data constitutes the reality check for research in the area. During the past few years, the International Conference on Data Warehousing and Knowledge Discovery (DaWaK) has become one of the most important international scientific events bringing together researchers, developers and practitioners. The DaWaK conferences served as a prominent forum for discussing latest research issues and experiences in developing and deploying data warehousing and knowledge d- covery systems, applications, and solutions. This year’s conference, the Ninth Inter- tional Conference on Data Warehousing and Knowledge Discovery (DaWaK 2007), built on this tradition of facilitating the cross-disciplinary exchange of ideas, expe- ence and potential research directions. DaWaK 2007 sought to disseminate innovative principles, methods, algorithms and solutions to challenging problems faced in the development of data warehousing, knowledge discovery and data mining applications.