Data mining and mathematical programming Panos M. Pardalos, Pierre Hansen, eds. CRM proceedings & lecture notes 45; CRM proceedings & [and] lecture notes 45.

Panos M. Pardalos And Pierre Hansen

ISBN 10: 0821843524 / ISBN 13: 9780821843529

Published by Providence, American Mathematical Society, 2008

About this Item

Ex-library with stamp and library-signature. GOOD condition, some traces of use. Ancien Exemplaire de bibliothèque avec signature et cachet. BON état, quelques traces d'usure. Ehem. Bibliotheksexemplar mit Signatur und Stempel. GUTER Zustand, ein paar Gebrauchsspuren. 68 DAT 9780821843529 Sprache: Englisch Gewicht in Gramm: 550. Seller Inventory # 2498789

Bibliographic Details

Title: Data mining and mathematical programming ...

Publisher: Providence, American Mathematical Society

Publication Date: 2008

Binding: Softcover

About this title

Synopsis:

Data mining aims at finding interesting, useful or profitable information in very large databases. The enormous increase in the size of available scientific and commercial databases (data avalanche) as well as the continuing and exponential growth in performance of present day computers make data mining a very active field. In many cases, the burgeoning volume of data sets has grown so large that it threatens to overwhelm rather than enlighten scientists. Therefore, traditional methods are revised and streamlined, complemented by many new methods to address challenging new problems. Mathematical Programming plays a key role in this endeavor. It helps us to formulate precise objectives (e.g., a clustering criterion or a measure of discrimination) as well as the constraints imposed on the solution (e.g., find a partition, a covering or a hierarchy in clustering). It also provides powerful mathematical tools to build highly performing exact or approximate algorithms. This book is based on lectures presented at the workshop on ""Data Mining and Mathematical Programming"" (October 10-13, 2006, Montreal) and will be a valuable scientific source of information to faculty, students, and researchers in optimization, data analysis and data mining, as well as people working in computer science, engineering and applied mathematics.