Language: English
Published by SAGE Publications Ltd, 2006
ISBN 10: 1586033948 ISBN 13: 9781586033941
Seller: medimops, Berlin, Germany
Condition: good. Befriedigend/Good: Durchschnittlich erhaltenes Buch bzw. Schutzumschlag mit Gebrauchsspuren, aber vollständigen Seiten. / Describes the average WORN book or dust jacket that has all the pages present.
Language: English
Published by SAGE Publications Ltd, 2006
ISBN 10: 1586033948 ISBN 13: 9781586033941
Seller: Hay-on-Wye Booksellers, Hay-on-Wye, HEREF, United Kingdom
Condition: Very Good. Used, some outer edges have minor scuffs, cover has light scratches, some outer pages have shelf wear, book content is in very good condition.
Language: English
Published by Südwestdeutscher Verlag für Hochschulschriften, 2010
ISBN 10: 3838113756 ISBN 13: 9783838113753
Seller: preigu, Osnabrück, Germany
Taschenbuch. Condition: Neu. A Domain-Independent Framework for Intelligent Recommendations | Design, Application and Evaluation of a Hybrid Machine Learning Framework using Case Studies within varied Domains | Jörn David | Taschenbuch | 340 S. | Englisch | 2010 | Südwestdeutscher Verlag für Hochschulschriften | EAN 9783838113753 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
Language: English
Published by SAGE Publications Ltd, 2006
ISBN 10: 1586033948 ISBN 13: 9781586033941
Seller: Basi6 International, Irving, TX, U.S.A.
Condition: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
Language: English
Published by Südwestdeutscher Verlag Für Hochschulschriften AG Co. KG, 2010
ISBN 10: 3838113756 ISBN 13: 9783838113753
Seller: AHA-BUCH GmbH, Einbeck, Germany
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Recommender systems assist the user in decision- making processes and automate information processing steps like the classification of artifacts. Intelligent recommendations help users to cope with the steadily growing information overload within the internet or when using information systems at their place of work, for instance. As an example, the recommendation techniques collaborative filtering and content-based filtering are mainly applied in the areas of e-Commerce and web navigation to recommend potentially relevant articles or websites. Recommender systems are either based on machine learning functions such as clustering, classification, and prediction or they are realized by symbolic methods like association rule mining, that is, by rule-based mechanisms in general. The hybrid and domain-independent framework developed in this dissertation called SymboConn is based on a recurrent neural network and provides a high generalization capability, flexibility, and robustness. We demonstrate its applicability by case studies in navigation recommendation, design pattern discovery, change impact analysis as well as time series prediction.