Fuzzy Preference Queries To Relational Databases

— —

Olivier Pivert (Irisa/enssat, Univ Of Rennes 1, France) Patrick Bosc (Irisa/enssat, Univ Of Rennes 1, France)

Fuzzy Preference Queries To Relational Databases

Olivier Pivert (Irisa/enssat, Univ Of Rennes 1, France), Patrick Bosc (Irisa/enssat, Univ Of Rennes 1, France)

$243.99

Hardback

Not in-store but you can order this
How long will it take?

Availability Information

We source books from suppliers in Australia and overseas. For books we don't currently have in stock, the time it takes to get them from our suppliers can vary widely - from a few days to a few months - so we check each book with each supplier to determine the expected time it will take to be supplied to us.

We then advise you accordingly. If the time taken to get any book is too long for you, you can let us know and we will cancel or adjust your order, and refund as required.

To find out the anticipated arrival time for specific items prior to ordering, please contact us by phone or email:

Phone +61 2 9264 3111, or 1800 4 BOOKS (1800 4 26657) if outside Sydney:
option 1 Abbey's Bookshop (Crime, History, Science, Kids & more) • info@abbeys.com.au
option 2 Language Book Centre (ESL & Foreign Languages) • language@abbeys.com.au
option 3 Galaxy Bookshop (Sci-fi, Fantasy, Romance, Graphic Novels) • sf@galaxybooks.com.au

QTY:

English

Imperial College Press
24 February 2012

Relational databases

The manipulation of databases is an integral part of a world which is becoming increasingly and pervasively information-focused. This book puts forward a suggestion to advocate preference queries and fuzzy sets as a central concern in database queries and offers an important contribution to the design of intelligent information systems. It provides a comprehensive study on fuzzy preference queries in the context of relational databases. Preference queries, a recent hot topic in database research, provide a basis for rank-ordering the items retrieved, which is especially valuable for large sets of answers.

This book aims to show that fuzzy set theory constitutes a highly expressive framework for modeling preference queries. It presents a study of the algorithmic aspects related to the evaluation of such queries in order to demonstrate that this framework offers a good trade-off between expressivity and efficiency. Numerous examples and proofs are liberally and lucidly demonstrated throughout, and greatly enhance the detailed theoretical aspects explored in the book.

Researchers working in databases will greatly benefit from this comprehensive and up-to-date study of fuzzy preference queries, and it will also become an invaluable reference point for postgraduate students interested in advanced database techniques.

The only other books which deal with this topic are edited books or conference proceedings which include a few contributions about some specific aspects of the question. This book provides a comprehensive view of the issue, starting with basic notions related to relational databases and fuzzy set theory, up to the detailed study of complex fuzzy queries and the way they can be efficiently processed. It is the compendium of more than 20 years of research by the authors who benefit from a great international recognition in the domain of intelligent information systems, on the subject.

By: Olivier Pivert (Irisa/enssat Univ Of Rennes 1 France), Patrick Bosc (Irisa/enssat, Univ Of Rennes 1, France)
Imprint: Imperial College Press
Country of Publication: United Kingdom
Dimensions: Height: 236mm, Width: 155mm, Spine: 25mm
Weight: 612g
ISBN: 9781848168695
ISBN 10: 1848168691
Pages: 348
Publication Date: 24 February 2012
Audience: College/higher education , Further / Higher Education
Format: Hardback
Publisher's Status: Active

Introduction; Reminders on Relational Databases; Basic Notions on Fuzzy Sets; Non-Fuzzy Approaches to Preference Queries: A Brief Overview; Simple Fuzzy Queries; Fuzzy Queries Involving Quantified Statements or Aggregates; Division and Antidivision of Fuzzy Relations; Bipolar Fuzzy Queries; Fuzzy Group By; Empty and Plethoric Answers.