9780367631871 - Recommender Systems: Algorithms and Applications (16 risultati)

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Condizione: New.

Condizione: New. xvii, 230 pages, illustrations.

Condizione: New. xvii, 230 pages, illustrations First edition Includes bibliographical references and index.

Condizione: New. In.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Condizione: New. xvii, 230 pages, illustrations.

Paperback / softback. Condizione: New. New copy - Usually dispatched within 4 working days.

Paperback. Condizione: Brand New. 248 pages. 9.18x6.12x9.21 inches. In Stock.

Paperback. Condizione: new. Paperback. Recommender systems use information filtering to predict user preferences. They are becoming a vital part of e-business and are used in a wide variety of industries, ranging from entertainment and social networking to information technology, tourism, education, agriculture, healthcare, manufacturing, and retail. Recommender Systems: Algorithms and Applications dives into the theoretical underpinnings of these systems and looks at how this theory is applied and implemented in actual systems. The book examines several classes of recommendation algorithms, including Machine learning algorithms Community detection algorithms Filtering algorithmsVarious efficient and robust product recommender systems using machine learning algorithms are helpful in filtering and exploring unseen data by users for better prediction and extrapolation of decisions. These are providing a wider range of solutions to such challenges as imbalanced data set problems, cold-start problems, and long tail problems. This book also looks at fundamental ontological positions that form the foundations of recommender systems and explain why certain recommendations are predicted over others. Techniques and approaches for developing recommender systems are also investigated. These can help with implementing algorithms as systems and include A latent-factor technique for model-based filtering systems Collaborative filtering approaches Content-based approachesFinally, this book examines actual systems for social networking, recommending consumer products, and predicting risk in software engineering projects. Recommender systems use information filtering to predict user preferences. They are becoming a vital part of e-business. Recommender Systems: Algorithms and Applications dives into the theoretical underpinnings of these systems and looks at how theory is applied and implemented in actual systems. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Paperback / softback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 526.

Paperback. Condizione: new. Paperback. Recommender systems use information filtering to predict user preferences. They are becoming a vital part of e-business and are used in a wide variety of industries, ranging from entertainment and social networking to information technology, tourism, education, agriculture, healthcare, manufacturing, and retail. Recommender Systems: Algorithms and Applications dives into the theoretical underpinnings of these systems and looks at how this theory is applied and implemented in actual systems. The book examines several classes of recommendation algorithms, including Machine learning algorithms Community detection algorithms Filtering algorithmsVarious efficient and robust product recommender systems using machine learning algorithms are helpful in filtering and exploring unseen data by users for better prediction and extrapolation of decisions. These are providing a wider range of solutions to such challenges as imbalanced data set problems, cold-start problems, and long tail problems. This book also looks at fundamental ontological positions that form the foundations of recommender systems and explain why certain recommendations are predicted over others. Techniques and approaches for developing recommender systems are also investigated. These can help with implementing algorithms as systems and include A latent-factor technique for model-based filtering systems Collaborative filtering approaches Content-based approachesFinally, this book examines actual systems for social networking, recommending consumer products, and predicting risk in software engineering projects. Recommender systems use information filtering to predict user preferences. They are becoming a vital part of e-business. Recommender Systems: Algorithms and Applications dives into the theoretical underpinnings of these systems and looks at how theory is applied and implemented in actual systems. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Taschenbuch. Condizione: Neu. Recommender Systems | Algorithms and Applications | P. Pavan Kumar (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2024 | CRC Press | EAN 9780367631871 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Recommender systems use information filtering to predict user preferences. They are becoming a vital part of e-business. Recommender Systems: Algorithms and Applications dives into the theoretical underpinnings of these systems and looks at how theory is applied and implemented in actual systems.