Social Web Artifacts for Boosting Recommenders : Theory and Implementation
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...
Uloženo v:
| Hlavní autor: | |
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| Médium: | Livre numérique |
| Jazyk: | Anglais |
| Vydáno: |
Cham :
Springer International Publishing
[20..].
Cham : Springer Nature |
| Vydání: | 1st ed. 2013. |
| Edice: | Studies in Computational Intelligence
487 |
| On-line přístup: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Poznámka: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Social Web Artifacts for Boosting Recommenders, Texte imprimé, 9783319005263 • Social Web Artifacts for Boosting Recommenders, Texte imprimé, 9783319032870 • Social Web Artifacts for Boosting Recommenders, Texte imprimé, 9783319005287 • Social Web Artifacts for Boosting Recommenders, Texte imprimé, 9783319005263 |
| Shrnutí: | 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 |
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| Popis jednotky: | Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| ISBN: | 9783319005270 |
| ISSN: | 1860-9503 |
| Přístup: | Accès en ligne pour les établissements français bénéficiaires des licences nationales Accès soumis à abonnement pour tout autre établissement Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 |