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Titlebook: Data Warehousing and Knowledge Discovery; 13th International C Alfredo Cuzzocrea,Umeshwar Dayal Conference proceedings 2011 Springer-Verlag

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书目名称Data Warehousing and Knowledge Discovery
副标题13th International C
编辑Alfredo Cuzzocrea,Umeshwar Dayal
视频video
概述Fast-track conference proceedings.State-of-the-art research.Up-to-date results
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Data Warehousing and Knowledge Discovery; 13th International C Alfredo Cuzzocrea,Umeshwar Dayal Conference proceedings 2011 Springer-Verlag
描述This book constitutes the refereed proceedings of the 13th International Conference on Data Warehousing and Knowledge Discovery, DaWak 2011 held in Toulouse, France in August/September 2011. The 37 revised full papers presented were carefully reviewed and selected from 119 submissions. The papers are organized in topical sections on physical and conceptual data warehouse models, data warehousing design methodologies and tools, data warehouse performance and optimization, pattern mining, matrix-based mining techniques and stream, sensor and time-series mining.
出版日期Conference proceedings 2011
关键词OLAP; data cleaning; data clustering; data streaming; privacy presevering data mining; algorithm analysis
版次1
doihttps://doi.org/10.1007/978-3-642-23544-3
isbn_softcover978-3-642-23543-6
isbn_ebook978-3-642-23544-3Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag GmbH Berlin Heidelberg 2011
The information of publication is updating

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OLAP Formulations for Supporting Complex Spatial Objects in Data Warehousesd other domains. Data warehouses help in modeling and mining large amounts of data from heterogeneous sources over an extended period of time. However incorporating spatial data into data warehouses leads to several challenges in data modeling, management and the mining of spatial information. New m
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Multidimensional Database Design from Document-Centric XML Documentshese documents are loosely structured XML documents mainly composed of text. This paper details conceptual design steps of multidimensional databases from such documents. With the use of an adapted multidimensional conceptual model, the design process allows the integration of data extracted from te
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: Requirement-Driven Generation of ETL and Multidimensional Conceptual Designsan appropriate conceptual, multidimensional design. Typically, this task is performed manually, through a series of interviews involving two different parties: the business analysts and technical designers. Producing an appropriate conceptual design is an error-prone task that undergoes several roun
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Complementing Data in the ETL Process, known as ETL (Extraction, Transformation, and Load), usually takes care of improving the data quality. However, it is not unusual to identify null values in a DW fact table during the ETL process, and this may impact negatively on the accuracy of data analyses results. Data imputation1 techniques
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