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PRINT ON DEMAND pp. 106. Codice articolo 1897146588
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.
Product Description: Book by Ekstrand Michael D Riedl John T Konstan Joseph A
Titolo: Collaborative Filtering Recommender Systems
Casa editrice: Now Publishers
Data di pubblicazione: 2011
Legatura: Brossura
Condizione: New
Da: preigu, Osnabrück, Germania
Taschenbuch. Condizione: Neu. PLSA BASED FRAMEWORK FOR HYBRID SOCIAL RECOMMENDER SYSTEMS | A mathematical framework to combine collaborative filtering and social network analysis | Erkin Eryol | Taschenbuch | Englisch | VDM Verlag Dr. Müller | EAN 9783639291636 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand. Codice articolo 107108497
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
Condizione: As New. Unread book in perfect condition. Codice articolo 47618918
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Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: As New. Unread book in perfect condition. Codice articolo 47618918
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Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: New. Codice articolo 47618918-n
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
Condizione: New. Codice articolo 47618918-n
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Da: Majestic Books, Hounslow, Regno Unito
Condizione: New. pp. 142. Codice articolo 394739633
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Da: Books Puddle, New York, NY, U.S.A.
Condizione: New. pp. 142 1st edition NO-PA16APR2015-KAP. Codice articolo 26401637486
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Da: Biblios, Frankfurt am main, HESSE, Germania
Condizione: New. pp. 142. Codice articolo 18401637476
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Da: preigu, Osnabrück, Germania
Buch. Condizione: Neu. Collaborative Filtering | Recommender Systems | Angshul Majumdar | Buch | Einband - fest (Hardcover) | Englisch | 2024 | CRC Press | EAN 9781032840826 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. Codice articolo 128870327
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Da: Revaluation Books, Exeter, Regno Unito
Hardcover. Condizione: Brand New. 152 pages. 9.19x6.13x9.21 inches. In Stock. Codice articolo x-103284082X
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