Recommender systems already exist in a variety of item domains: entertainment, commerce, news and more. One should expect these systems to become more useful and essential as knowledge volume rapidly grows. The book describes a unique research, demonstrating that the likelihood that users of a social collaborative system would accept recommendations from recommender systems depends on the type of group that made the recommendations and on the users' involvement in the formation of that group. A longitudinal analysis indicates a positive learning curve for experienced users, who acquire a tendency to prefer 'friends group' over 'neighbors group' as their experience with the system increases. Also, users chose their own group to participate in the advising group significantly more than other groups. The main implication of these findings for the development of future recommender systems is to enhance the involvement of recommendation seekers in the process of forming the advising group. Also, developers of recommender systems should consider increasing users' control over relevant characteristics of the members of this group.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Yuval Dan-Gur is a researcher in the IS domain. Teaches in academic institutions and served as V.P. for Development at High-Tech organizations. Holds Ph.D. in Information Systems, MSc. in Industrial Engineering and BSc. in Electrical Engineering. Developed recommender systems and is engaged in prestigious workshops for senior executives.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Recommender systems already exist in a variety of item domains: entertainment, commerce, news and more. One should expect these systems to become more useful and essential as knowledge volume rapidly grows. The book describes a unique research, demonstrating that the likelihood that users of a social collaborative system would accept recommendations from recommender systems depends on the type of group that made the recommendations and on the users' involvement in the formation of that group. A longitudinal analysis indicates a positive learning curve for experienced users, who acquire a tendency to prefer 'friends group' over 'neighbors group' as their experience with the system increases. Also, users chose their own group to participate in the advising group significantly more than other groups. The main implication of these findings for the development of future recommender systems is to enhance the involvement of recommendation seekers in the process of forming the advising group. Also, developers of recommender systems should consider increasing users' control over relevant characteristics of the members of this group. 220 pp. Englisch. N° de réf. du vendeur 9783838301334
Quantité disponible : 2 disponible(s)
Vendeur : moluna, Greven, Allemagne
Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Recommender systems already exist in a variety of item domains: entertainment, commerce, news and more. One should expect these systems to become more useful and essential as knowledge volume rapidly grows. The book describes a unique research, demonstratin. N° de réf. du vendeur 5410875
Quantité disponible : Plus de 20 disponibles
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Recommender systems already exist in a variety of item domains: entertainment, commerce, news and more. One should expect these systems to become more useful and essential as knowledge volume rapidly grows. The book describes a unique research, demonstrating that the likelihood that users of a social collaborative system would accept recommendations from recommender systems depends on the type of group that made the recommendations and on the users' involvement in the formation of that group. A longitudinal analysis indicates a positive learning curve for experienced users, who acquire a tendency to prefer 'friends group' over 'neighbors group' as their experience with the system increases. Also, users chose their own group to participate in the advising group significantly more than other groups. The main implication of these findings for the development of future recommender systems is to enhance the involvement of recommendation seekers in the process of forming the advising group. Also, developers of recommender systems should consider increasing users' control over relevant characteristics of the members of this group.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 220 pp. Englisch. N° de réf. du vendeur 9783838301334
Quantité disponible : 1 disponible(s)
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Recommender systems already exist in a variety of item domains: entertainment, commerce, news and more. One should expect these systems to become more useful and essential as knowledge volume rapidly grows. The book describes a unique research, demonstrating that the likelihood that users of a social collaborative system would accept recommendations from recommender systems depends on the type of group that made the recommendations and on the users' involvement in the formation of that group. A longitudinal analysis indicates a positive learning curve for experienced users, who acquire a tendency to prefer 'friends group' over 'neighbors group' as their experience with the system increases. Also, users chose their own group to participate in the advising group significantly more than other groups. The main implication of these findings for the development of future recommender systems is to enhance the involvement of recommendation seekers in the process of forming the advising group. Also, developers of recommender systems should consider increasing users' control over relevant characteristics of the members of this group. N° de réf. du vendeur 9783838301334
Quantité disponible : 1 disponible(s)
Vendeur : preigu, Osnabrück, Allemagne
Taschenbuch. Etat : Neu. Controlled 'Friends Group' in Recommender Systems | Recommender Systems: Concept, Theory and Practice | Yuval Dan-Gur | Taschenbuch | 220 S. | Englisch | 2013 | LAP LAMBERT Academic Publishing | EAN 9783838301334 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. N° de réf. du vendeur 101562615
Quantité disponible : 5 disponible(s)
Vendeur : Mispah books, Redhill, SURRE, Royaume-Uni
paperback. Etat : Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book. N° de réf. du vendeur ERICA80038383013316
Quantité disponible : 1 disponible(s)