Librería: Hay-on-Wye Booksellers, Hay-on-Wye, HEREF, Reino Unido
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Añadir al carritoCondición: 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.
Librería: medimops, Berlin, Alemania
EUR 12,64
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Añadir al carritoCondición: 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.
Publicado por Südwestdeutscher Verlag für Hochschulschriften AG Co. KG, 2015
ISBN 10: 3838113756 ISBN 13: 9783838113753
Idioma: Inglés
Librería: preigu, Osnabrück, Alemania
EUR 75,50
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Añadir al carritoTaschenbuch. Condición: 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 | 2015 | Südwestdeutscher Verlag für Hochschulschriften AG Co. KG | EAN 9783838113753 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.
Librería: Basi6 International, Irving, TX, Estados Unidos de America
EUR 160,08
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Añadir al carritoCondición: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
Publicado por Südwestdeutscher Verlag Für Hochschulschriften AG Co. KG, 2010
ISBN 10: 3838113756 ISBN 13: 9783838113753
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 89,90
Cantidad disponible: 1 disponibles
Añadir al carritoTaschenbuch. Condición: 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.