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Bücher Englische Bücher Wissen & Bildung Naturwissenschaft, Medizin, Informatik, Technik Technik Allg. & Lexika Social Web Artifacts for Boosting Recommenders
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Beschreibung
Recommender systems, software programs that learn from human behavior and make predictions of what products we are expected to appreciate and purchase, have become an integral part of our everyday life. They proliferate across electronic commerce around the globe and exist for virtually all sorts of consumable goods, such as books, movies, music, or clothes. At the same time, a new evolution on… the Web has started to take shape, commonly known as the “Web 2.0” or the “Social Web”: Consumer-generated media has become rife, social networks have emerged and are pulling significant shares of Web traffic. In line with these developments, novel information and knowledge artifacts have become readily available on the Web, created by the collective effort of millions of people. This textbook presents approaches to exploit the new Social Web fountain of knowledge, zeroing in first and foremost on two of those information artifacts, namely classification taxonomies and trust networks. These two are used to improve the performance of product-focused recommender systems: While classification taxonomies are appropriate means to fight the sparsity problem prevalent in many productive recommender systems, interpersonal trust ties – when used as proxies for interest similarity – are able to mitigate the recommenders' scalability problem. Dieses Produkt haben wir gerade leider nicht auf Lager.
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Technische Daten
Erscheinungsdatum
31.05.2013
Sprache
Englisch
EAN
9783319005263
Herausgeber
Springer International Publishing
Serien- oder Bandtitel
Studies in Computational Intelligence
Sonderedition
Nein
Autor
Cai-Nicolas Ziegler
Seitenanzahl
187
Einbandart
Gebundene Ausgabe
Buch Untertitel
Theory and Implementation
Schlagwörter
Collaborative Filtering, Collective Intelligence, Content Discovery Platform, Enterprise Bookmarking, Personalized Marketing, Recommender Platform, Recommender Systems, Web Recommender Systems
Thema-Inhalt
UYQ - Künstliche Intelligenz
UNF - Data Mining
UYQE - Wissensbasierte Systeme, Expertensysteme
Höhe
235 mm
Breite
15.5 cm
Transparenz & Sicherheit
Hersteller: Springer, Europaplatz 3, Heidelberg, Deutschland, 69115, ProductSafety@springernature.com, Springer Nature Customer Service Center GmbH
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