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Titlebook: Hyper-lattice Algebraic Model for Data Warehousing; Soumya Sen,Agostino Cortesi,Nabendu Chaki Book 2016 The Author(s) 2016 Algebraic Struc

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书目名称Hyper-lattice Algebraic Model for Data Warehousing
编辑Soumya Sen,Agostino Cortesi,Nabendu Chaki
视频videohttp://file.papertrans.cn/431/430573/430573.mp4
概述Introduces a new algebraic structure in hyper lattice.Presents a traversal mechanism in an algorithm for the cuboids in data warehouse to take advantage of space and time complexity.Shows how to propo
丛书名称SpringerBriefs in Applied Sciences and Technology
图书封面Titlebook: Hyper-lattice Algebraic Model for Data Warehousing;  Soumya Sen,Agostino Cortesi,Nabendu Chaki Book 2016 The Author(s) 2016 Algebraic Struc
描述This book presents Hyper-lattice, a new algebraic model for partially ordered sets, and an alternative to lattice. The authors analyze some of the shortcomings of conventional lattice structure and propose a novel algebraic structure in the form of Hyper-lattice to overcome problems with lattice. They establish how Hyper-lattice supports dynamic insertion of elements in a partial order set with a partial hierarchy between the set members. The authors present the characteristics and the different properties, showing how propositions and lemmas formalize Hyper-lattice as a new algebraic structure.
出版日期Book 2016
关键词Algebraic Structures; Data Analysis; Data Warehousing; Hyper Lattice; OLAP; Online Analytical Processing
版次1
doihttps://doi.org/10.1007/978-3-319-28044-8
isbn_softcover978-3-319-28042-4
isbn_ebook978-3-319-28044-8Series ISSN 2191-530X Series E-ISSN 2191-5318
issn_series 2191-530X
copyrightThe Author(s) 2016
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Applications of Hyper-lattice in Real Life,ferent case studies are considered on five different application environments. Within a short space, we have considered variations common in data warehouses and how to use Hyper Lattice to represent, and model such situations.
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https://doi.org/10.1007/978-3-319-28044-8Algebraic Structures; Data Analysis; Data Warehousing; Hyper Lattice; OLAP; Online Analytical Processing
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Generating Co-operative Queries Over Concept Hierarchies,es. Concept Hierarchy presents the information of a same dimension in different abstracted levels. This abstraction allows us to identify the same data in multiple granularities and from different users’ perspectives. Conventional query execution retrieves information in one abstracted form only for
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Conclusions,imensional data archive in a way which is more flexible and comprehensive as compared to conventional Lattice structures. Thus, Hyper-lattice can be used as a model multi-dimensional data to be stored and accessed for online data analytics.
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