Integrating OLAP and Ranking : The Ranking-Cube Methodology

Dong Xin

ISBN 10: 3639157990 / ISBN 13: 9783639157994

Published by VDM Verlag Dr. Müller, 2009

About this Item

nach der Bestellung gedruckt Neuware - Printed after ordering - 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 off-line materialization and semi online computation. 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 (e.g., skyline queries).

Seller Inventory # 9783639157994

Bibliographic Details

• Title: Integrating OLAP and Ranking : The Ranking-Cube Methodology
• Publisher: VDM Verlag Dr. Müller
• Publication Date: 2009
• Language: English
• ISBN 10: 3639157990
• ISBN 13: 9783639157994
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 22W x 15H x 1D centimeters 22 centimeters width by 15 centimeters height by 1 centimeters depth
• Weight: 284 grams

About this title

Synopsis

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 off-line materialization and semi online computation. 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 (e.g., skyline queries).

About the Author

Dong Xin is a researcher in the Data Management, Exploration and Mining Group at Microsoft Research. He completed his Ph.D. in Computer Science at the University of Illinois at Urbana- Champaign in 2007. His research interests include data mining, data warehousing and database systems.