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Recommender Systems Learning by Manouselis Nikos (52 results)
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Recommender Systems for Technology Enhanced Learning. Research Trends and Applications.
Published by New York, NY ; s.l., Springer New York/Imprint: Springer., 2014
ISBN 10: 1493946560 ISBN 13: 9781493946563
Language: English
Seller: Universitätsbuchhandlung Herta Hold GmbH, Berlin, Germany
Association Member: GIAQ ILAB VDA
Seller rating 5 out of 5 stars
ed. 2014. XIV, 306 p. Softcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Stemped. Sprache: Englisch.
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Condition: New.
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Condition: New. SUPER FAST SHIPPING.
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Condition: As New. Unread book in perfect condition.
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Recommender Systems for Learning (SpringerBriefs in Electrical and Computer Engineering)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
Condition: New. In.
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Paperback. Condition: New.
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Recommender Systems for Learning
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New.
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Condition: New. pp. 90.
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Recommender Systems for Learning
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition.
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Recommender Systems for Learning
Published by Springer-Verlag New York Inc, 2012
ISBN 10: 1461443601 ISBN 13: 9781461443605
Language: English
Paperback. Condition: Brand New. 90 pages. 9.00x6.00x0.20 inches. In Stock.
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Condition: New. SUPER FAST SHIPPING.
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Condition: New. SUPER FAST SHIPPING.
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Recommender Systems for Technology Enhanced Learning: Research Trends and Applications
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
Condition: New. In.
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Recommender Systems for Technology Enhanced Learning: Research Trends and Applications
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
Condition: New. In.
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Recommender Systems for Learning
Published by Springer New York, Springer US, 2012
ISBN 10: 1461443601 ISBN 13: 9781461443605
Language: English
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 1.
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Taschenbuch. Condition: Neu. Recommender Systems for Learning | Nikos Manouselis (u. a.) | Taschenbuch | xi | Englisch | 2012 | Springer US | EAN 9781461443605 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Recommender Systems for Technology Enhanced Learning : Research Trends and Applications
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New.
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Condition: New. pp. 306.
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Condition: New. pp. 322.
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Recommender Systems for Technology Enhanced Learning: Research Trends and Applications
Published by Springer-Verlag New York Inc, 2016
ISBN 10: 1493946560 ISBN 13: 9781493946563
Language: English
Paperback. Condition: Brand New. reprint edition. 320 pages. 9.25x6.10x0.71 inches. In Stock.
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Hardcover. Condition: Neu. Neu Neuware, auf Lager - As an area, Technology Enhanced Learning (TEL) aims to design, develop and test socio-technical innovations that will support and enhance learning practices of individuals and organizations. Information retrieval is a pivotal activity in TEL and the deployment of recommender systems has attracted increased interest during the past years.Recommendation methods, techniques and systems open an interesting new approach to facilitate and support learning and teaching. The goal is to develop, deploy and evaluate systems that provide learners and teachers with meaningful guidance in order to help identify suitable learning resources from a potentially overwhelming variety of choices.Contributions address the following topics: i) user and item data that can be used to support learning recommendation systems and scenarios, ii) innovative methods and techniques for recommendation purposes in educational settings and iii) examples of educational platforms and tools where recommendations are incorporated.
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Hardcover. Condition: Brand New. 320 pages. 9.50x6.25x0.75 inches. In Stock.
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Taschenbuch. Condition: Neu. Recommender Systems for Technology Enhanced Learning | Research Trends and Applications | Nikos Manouselis (u. a.) | Taschenbuch | xiv | Englisch | 2016 | Springer US | EAN 9781493946563 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Recommender Systems for Technology Enhanced Learning
Published by Springer New York, Springer US Sep 2016, 2016
ISBN 10: 1493946560 ISBN 13: 9781493946563
Language: English
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. Neuware -As an area, Technology Enhanced Learning (TEL) aims to design, develop and test socio-technical innovations that will support and enhance learning practices of individuals and organizations. Information retrieval is a pivotal activity in TEL and the deployment of recommender systems has attracted increased interest during the past years.Recommendation methods, techniques and systems open an interesting new approach to facilitate and support learning and teaching. The goal is to develop, deploy and evaluate systems that provide learners and teachers with meaningful guidance in order to help identify suitable learning resources from a potentially overwhelming variety of choices.Contributions address the following topics: i) user and item data that can be used to support learning recommendation systems and scenarios, ii) innovative methods and techniques for recommendation purposes in educational settings and iii) examples of educational platforms and tools where recommendations are incorporated.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 320 pp. Englisch.
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Recommender Systems for Technology Enhanced Learning
Published by Springer New York, Springer US Apr 2014, 2014
ISBN 10: 1493905295 ISBN 13: 9781493905294
Language: English
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Buch. Condition: Neu. Neuware -As an area, Technology Enhanced Learning (TEL) aims to design, develop and test socio-technical innovations that will support and enhance learning practices of individuals and organizations. Information retrieval is a pivotal activity in TEL and the deployment of recommender systems has attracted increased interest during the past years.Recommendation methods, techniques and systems open an interesting new approach to facilitate and support learning and teaching. The goal is to develop, deploy and evaluate systems that provide learners and teachers with meaningful guidance in order to help identify suitable learning resources from a potentially overwhelming variety of choices.Contributions address the following topics: i) user and item data that can be used to support learning recommendation systems and scenarios, ii) innovative methods and techniques for recommendation purposes in educational settings and iii) examples of educational platforms and tools where recommendations are incorporated.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 320 pp. Englisch.
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Recommender Systems for Technology Enhanced Learning : Research Trends and Applications
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition.
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Recommender Systems for Technology Enhanced Learning : Research Trends and Applications
Published by Springer New York, Springer US, 2016
ISBN 10: 1493946560 ISBN 13: 9781493946563
Language: English
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - As an area, Technology Enhanced Learning (TEL) aims to design, develop and test socio-technical innovations that will support and enhance learning practices of individuals and organizations. Information retrieval is a pivotal activity in TEL and the deployment of recommender systems has attracted increased interest during the past years.Recommendation methods, techniques and systems open an interesting new approach to facilitate and support learning and teaching. The goal is to develop, deploy and evaluate systems that provide learners and teachers with meaningful guidance in order to help identify suitable learning resources from a potentially overwhelming variety of choices.Contributions address the following topics: i) user and item data that can be used to support learning recommendation systems and scenarios, ii) innovative methods and techniques for recommendation purposes in educational settings and iii) examples of educational platforms and tools where recommendations are incorporated.
