Chiudi

Aggiungi l'articolo in

Chiudi
Aggiunto

L’articolo è stato aggiunto alla lista dei desideri

Chiudi

Crea nuova lista

Offerta imperdibile
Collaborative Filtering Recommender Systems - Michael D. Ekstrand,John T. Riedl,Joseph A. Konstan - cover
Collaborative Filtering Recommender Systems - Michael D. Ekstrand,John T. Riedl,Joseph A. Konstan - cover
Dati e Statistiche
Wishlist Salvato in 0 liste dei desideri
Collaborative Filtering Recommender Systems
Disponibilità in 10 giorni lavorativi
112,33 €
112,33 €
Disp. in 10 gg
Chiudi

Altre offerte vendute e spedite dai nostri venditori

Altri venditori
Prezzo e spese di spedizione
ibs
Spedizione Gratis
112,33 €
Vai alla scheda completa
Altri venditori
Prezzo e spese di spedizione
ibs
Spedizione Gratis
112,33 €
Vai alla scheda completa
Altri venditori
Prezzo e spese di spedizione
Chiudi
ibs
Chiudi

Tutti i formati ed edizioni

Chiudi
Collaborative Filtering Recommender Systems - Michael D. Ekstrand,John T. Riedl,Joseph A. Konstan - cover
Chiudi

Promo attive (0)

Descrizione


Collaborative Filtering Recommender Systems discusses a wide variety of the recommender choices available and their implications, providing both practitioners and researchers with an introduction to the important issues underlying recommenders and current best practices for addressing these issues. Recommender systems are an important part of the information and e-commerce ecosystem. They represent a powerful method for enabling users to filter through large information and product spaces. Nearly two decades of research on collaborative filtering have led to a varied set of algorithms and a rich collection of tools for evaluating their performance. Research in the field is moving in the direction of a richer understanding of how recommender technology may be embedded in specific domains. The differing personalities exhibited by different recommender algorithms show that recommendation is not a one-size-fits-all problem. Specific tasks, information needs, and item domains represent unique problems for recommenders, and design and evaluation of recommenders needs to be done based on the user tasks to be supported. Effective deployments must begin with careful analysis of prospective users and their goals. Based on this analysis, system designers have a host of options for the choice of algorithm and for its embedding in the surrounding user experience. This paper discusses a wide variety of the choices available and their implications, aiming to provide both practicioners and researchers with an introduction to the important issues underlying recommenders and current best practices for addressing these issues.
Leggi di più Leggi di meno

Dettagli

Foundations and Trends (R) in Human-Computer Interaction
2011
Paperback / softback
106 p.
Testo in English
234 x 156 mm
162 gr.
9781601984425
Chiudi
Aggiunto

L'articolo è stato aggiunto al carrello

Chiudi

Aggiungi l'articolo in

Chiudi
Aggiunto

L’articolo è stato aggiunto alla lista dei desideri

Chiudi

Crea nuova lista

Chiudi

Chiudi

Siamo spiacenti si è verificato un errore imprevisto, la preghiamo di riprovare.

Chiudi

Verrai avvisato via email sulle novità di Nome Autore