Recommender Systems
Contenu
- Titre
- Recommender Systems
- Date de soumission
- 30 juin 2017, 18:58:54 +00:00
- Est référencé par
- MQ2G6PMD
- Résumé
- Acclaimed by various content platforms (books, music, movies) and auction sites online, recommendation systems are key elements of digital strategies. If development was originally intended for the performance of information systems, the issues are now massively moved on logical optimization of the customer relationship, with the main objective to maximize potential sales. On the transdisciplinary approach, engines and recommender systems brings together contributions linking information science and communications, marketing, sociology, mathematics and computing. It deals with the understanding of the underlying models for recommender systems and describes their historical perspective. It also analyzes their development in the content offerings and assesses their impact on user behavior.
- numéro d’édition
- 1
- Editeur
- Wiley-ISTE
- Date
- 4 décembre 2014
- nombre de pages
- 252
- Langue
- Anglais
- Source
- Amazon
- is compiled by
- Lucky Semiosis
- Complexité
-
221
- Date de modification
- 8 septembre 2023, 06:53:10 +00:00
- Détails de la complexité
- Physique,1,,,,,15,15
- Physique,2,,,,,19,38
- Actant,2,,,,,4,8
- Concept,1,,,,,14,14
- Concept,2,,,,,19,38
- Rapport,1,1,Physique,Concept,properties,14,14
- Rapport,1,1,Physique,Physique,values,14,14
- Rapport,1,1,Physique,Actant,dcterms:creator,3,3
- Rapport,2,2,Actant,Concept,properties,19,38
- Rapport,2,2,Actant,Physique,values,19,38
- Rapport,1,1,Physique,Actant,cito:isCompiledBy,1,1
- Totaux de la complexité
- Physique,2,1,2,34,53
- Actant,1,2,2,4,8
- Concept,2,1,2,33,52
- Rapport,6,1,2,70,108
- Existence,11,1,2,141,221
- Collections
- Zotero
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