Results 301 to 310 of about 173,446 (343)

High-dimensional Data Cubes

ACM Transactions on Database Systems
We introduce an approach to supporting high-dimensional data cubes at interactive query speeds and moderate storage cost. Our approach is based on binary(-domain) data cubes that are judiciously partially materialized; the missing information can be quickly approximated using statistical or linear programming techniques.
Sachin Basil John, Christoph Koch, Peter Lindner   +2 more
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Range cube: efficient cube computation by exploiting data correlation

Proceedings. 20th International Conference on Data Engineering, 2004
Data cube computation and representation are prohibitively expensive in terms of time and space. Prior work has focused on either reducing the computation time or condensing the representation of a data cube. We introduce range cubing as an efficient way to compute and compress the data cube without any loss of precision.
null Ying Feng, D. Agrawal, A. El Abbadi, A. Metwally   +3 more
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Dynamic Multidimensional Data Cubes

2003
Data cubes are ubiquitous tools in data warehousing, online analytical processing, and decision support applications. Based on a selection of pre-computed and materialized aggregate values, they can dramatically speed up aggregation and summarization over large data collections.
Mirek Riedewald, Divyakant Agrawal, Amr El Abbadi   +2 more
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Condensed cube: an effective approach to reducing data cube size

Proceedings 18th International Conference on Data Engineering, 2003
Pre-computed data cube facilitates OLAP (on-line analytical processing). It is well-known that data cube computation is an expensive operation. While most algorithms have been devoted to optimizing memory management and reducing computation costs, less work has addressed a fundamental issue: the size of a data cube is huge when a large base relation ...
null Wei Wang, null Jianlin Feng, null Hongjun Lu, J.X. Yu   +3 more
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Extracting semantics from data cubes using cube transversals and closures

Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '03, 2003
In this paper we propose a lattice-based approach intended for extracting semantics from datacubes: borders of version spaces for supervised classification, closed cube lattice to summarize the semantics of datacubes w.r.t. COUNT, SUM, and covering graph of the quotient cube as a visualization tool of minimal multidimensional associations.
Alain Casali, Rosine Cicchetti, Lotfi Lakhal   +2 more
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Data Cube Compression Techniques

2009
OnLine Analytical Processing (OLAP) research issues (Gray, Chaudhuri, Bosworth, Layman, Reichart & Venkatrao, 1997) such as data cube modeling, representation, indexing and management have traditionally attracted a lot of attention from the Data Warehousing research community.
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Data Cubes

2023
Edzer Pebesma, Roger Bivand
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Relationships in semantic data cubes

2020
<p><span>Linked data is a method for publishing structured data in a way that </span>also expresses its semantics. This semantic description is implemented <span>by the use of vocabularies, which are usually specified by the W3C as web standards.
Alexandr Mansurov, Olga Majlingova
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Data Cube Is Dead, Long Life to Data Cube in the Age of Web Data

2019
In a short time, the data warehouse (DW) technology took an important place in the academic and industrial landscapes. This place materialized in the large majority of engineering and management schools that adopted it in their curriculum and in the small, medium-size and large companies that enhanced their decision making capabilities thanks to it ...
Khouri, Selma, Berkani, Nabila, Bellatreche, Ladjel, Lanasri, Dihia   +3 more
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A Join-Like Operator to Combine Data Cubes and Answer Queries from Multiple Data Cubes

ACM Transactions on Database Systems, 2014
In order to answer a “joint” query from multiple data cubes, Pourabass and Shoshani [2007] distinguish the data cube on the measure of interest (called the “primary” data cube) from the other data cubes (called “proxy” data cubes) that are used to involve the dimensions (in the query) not in the primary data cube. They demonstrate in study
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