University of Illinois Urbana-Champaign

Integrating OLAP and Ranking: The Ranking-Cube Methodology

Xin, Dong

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Integrating OLAP and Ranking The Ranking-Cube Methodology.pdf

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https://hdl.handle.net/2142/11355

Description

Title
Integrating OLAP and Ranking: The Ranking-Cube Methodology
Author(s)
Xin, Dong
Issue Date
2007-08
Keyword(s)
database
Date of Ingest
2009-04-22T16:03:00Z
Abstract
Recent years have witnessed an enormous growth of data in business, industry, and Web applications. Database search often returns a large collection of results, which poses challenges to both efficient query processing and effective digest of the query results. To address this problem, ranked search has been introduced to database systems. We study the problem of On-Line Analytical Processing (OLAP) of ranked queries, where ranked queries are conducted in the arbitrary subset of data defined by multi-dimensional selections. While pre-computation and multi-dimensional aggregation is the standard solution for OLAP, materializing dynamic ranking results is unrealistic because the ranking criteria are not known until the query time. To overcome such difficulty, we develop a new ranking cube method that performs semi on-line materialization and semi online computation in this thesis. Its complete life cycle, including cube construction, incremental maintenance, and query processing, is also discussed. We further extend the ranking cube in three dimensions. First, how to answer queries in high-dimensional data. Second, how to answer queries which involves joins over multiple relations. Third, how to answer general preference queries (besides ranked queries, such as skyline queries). Our performance studies show that ranking-cube is orders of magnitude faster than previous approaches.
Type of Resource
text
Genre of Resource
Technical Report
Permalink
http://hdl.handle.net/2142/11355
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