A Dynamic Multi-Algorithm Collaborative-Filtering System (Paperback)
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| Preise | 2013 | 2014 | 2015 | 2019 |
|---|---|---|---|---|
| Schnitt | Fr. 65.71 (€ 67.14)¹ | Fr. 79.24 (€ 80.96)¹ | Fr. 77.40 (€ 79.08)¹ | Fr. 69.94 (€ 71.47)¹ |
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A Dynamic Multi-Algorithm Collaborative-Filtering System (Paperback) (2013)
DE PB NW RPISBN: 9783659399619 bzw. 3659399612, in Deutsch, LAP Lambert Academic Publishing, United States, Taschenbuch, neu, Nachdruck.
Lieferung aus: Deutschland, Versandkostenfrei.
Von Händler/Antiquariat, The Book Depository EURO [60485773], Slough, United Kingdom.
Language: English Brand New Book ***** Print on Demand *****.Nowadays users have access to an immense number of media content. They are able to consume thousands of TV channels and millions of video clips from online portals like YouTube. Due to the immense number of available content, users can have the problem to find content of interest. Recommendation systems are able to filter the immense number of recommendations and they are able to recommend content which fits to the interests of users. However, this research work presents a newly developed recommendation system which is able to increase the accuracy of predictions for recommendations. The newly developed recommendation system uses several algorithms and dynamically selects the most accurate algorithm. The system takes state-of-the-art algorithms and newly developed collaborative-filtering algorithms into account. The research work of this thesis proves that a dynamic selection of the most accurate filtering algorithm by considering more algorithms is able to increase the accuracy of the predictions significantly.
Von Händler/Antiquariat, The Book Depository EURO [60485773], Slough, United Kingdom.
Language: English Brand New Book ***** Print on Demand *****.Nowadays users have access to an immense number of media content. They are able to consume thousands of TV channels and millions of video clips from online portals like YouTube. Due to the immense number of available content, users can have the problem to find content of interest. Recommendation systems are able to filter the immense number of recommendations and they are able to recommend content which fits to the interests of users. However, this research work presents a newly developed recommendation system which is able to increase the accuracy of predictions for recommendations. The newly developed recommendation system uses several algorithms and dynamically selects the most accurate algorithm. The system takes state-of-the-art algorithms and newly developed collaborative-filtering algorithms into account. The research work of this thesis proves that a dynamic selection of the most accurate filtering algorithm by considering more algorithms is able to increase the accuracy of the predictions significantly.
2
Symbolbild
A dynamic multi-algorithm collaborative-filtering system (2013)
DE PB NW RPISBN: 9783659399619 bzw. 3659399612, in Deutsch, Taschenbuch, neu, Nachdruck.
Von Händler/Antiquariat, AHA-BUCH GmbH [51283250], Einbeck, NDS, Germany.
This item is printed on demand - Print on Demand Titel. - Nowadays users have access to an immense number of media content. They are able to consume thousands of TV channels and millions of video clips from online portals like YouTube. Due to the immense number of available content, users can have the problem to find content of interest. Recommendation systems are able to filter the immense number of recommendations and they are able to recommend content which fits to the interests of users. However, this research work presents a newly developed recommendation system which is able to increase the accuracy of predictions for recommendations. The newly developed recommendation system uses several algorithms and dynamically selects the most accurate algorithm. The system takes state-of-the-art algorithms and newly developed collaborative-filtering algorithms into account. The research work of this thesis proves that a dynamic selection of the most accurate filtering algorithm by considering more algorithms is able to increase the accuracy of the predictions significantly. 232 pp. Englisch.
This item is printed on demand - Print on Demand Titel. - Nowadays users have access to an immense number of media content. They are able to consume thousands of TV channels and millions of video clips from online portals like YouTube. Due to the immense number of available content, users can have the problem to find content of interest. Recommendation systems are able to filter the immense number of recommendations and they are able to recommend content which fits to the interests of users. However, this research work presents a newly developed recommendation system which is able to increase the accuracy of predictions for recommendations. The newly developed recommendation system uses several algorithms and dynamically selects the most accurate algorithm. The system takes state-of-the-art algorithms and newly developed collaborative-filtering algorithms into account. The research work of this thesis proves that a dynamic selection of the most accurate filtering algorithm by considering more algorithms is able to increase the accuracy of the predictions significantly. 232 pp. Englisch.
3
Symbolbild
A dynamic multi-algorithm collaborative-filtering system (2013)
DE PB NW RPISBN: 9783659399619 bzw. 3659399612, in Deutsch, Lap Lambert Academic Publishing Jun 2013, Taschenbuch, neu, Nachdruck.
Von Händler/Antiquariat, AHA-BUCH GmbH [51283250], Einbeck, Germany.
This item is printed on demand - Print on Demand Titel. - Nowadays users have access to an immense number of media content. They are able to consume thousands of TV channels and millions of video clips from online portals like YouTube. Due to the immense number of available content, users can have the problem to find content of interest. Recommendation systems are able to filter the immense number of recommendations and they are able to recommend content which fits to the interests of users. However, this research work presents a newly developed recommendation system which is able to increase the accuracy of predictions for recommendations. The newly developed recommendation system uses several algorithms and dynamically selects the most accurate algorithm. The system takes state-of-the-art algorithms and newly developed collaborative-filtering algorithms into account. The research work of this thesis proves that a dynamic selection of the most accurate filtering algorithm by considering more algorithms is able to increase the accuracy of the predictions significantly. 232 pp. Englisch.
This item is printed on demand - Print on Demand Titel. - Nowadays users have access to an immense number of media content. They are able to consume thousands of TV channels and millions of video clips from online portals like YouTube. Due to the immense number of available content, users can have the problem to find content of interest. Recommendation systems are able to filter the immense number of recommendations and they are able to recommend content which fits to the interests of users. However, this research work presents a newly developed recommendation system which is able to increase the accuracy of predictions for recommendations. The newly developed recommendation system uses several algorithms and dynamically selects the most accurate algorithm. The system takes state-of-the-art algorithms and newly developed collaborative-filtering algorithms into account. The research work of this thesis proves that a dynamic selection of the most accurate filtering algorithm by considering more algorithms is able to increase the accuracy of the predictions significantly. 232 pp. Englisch.
4
Symbolbild
A dynamic multi-algorithm collaborative-filtering system
DE PB NWISBN: 9783659399619 bzw. 3659399612, in Deutsch, Taschenbuch, neu.
Von Händler/Antiquariat, BuySomeBooks [52360437], Las Vegas, NV, U.S.A.
This item is printed on demand. Paperback. Nowadays users have access to an immense number of media content. They are able to consume thousands of TV channels and millions of video clips from online portals like YouTube. Due to the immense number of available content, users can have the problem to find content of interest. Recommendation systems are able to filter the immense number of recommendations and they are able to recommend content which fits to the interests of users. However, this research work presents a newly developed recommendation system which is able to increase the accuracy of predictions for recommendations. The newly developed recommendation system uses several algorithms and dynamically selects the most accurate algorithm. The system takes state-of-the-art algorithms and newly developed collaborative-filtering algorithms into account. The research work of this thesis proves that a dynamic selection of the most accurate filtering algorithm by considering more algorithms is able to increase the accuracy of the predictions significantly. This item ships from La Vergne,TN.
This item is printed on demand. Paperback. Nowadays users have access to an immense number of media content. They are able to consume thousands of TV channels and millions of video clips from online portals like YouTube. Due to the immense number of available content, users can have the problem to find content of interest. Recommendation systems are able to filter the immense number of recommendations and they are able to recommend content which fits to the interests of users. However, this research work presents a newly developed recommendation system which is able to increase the accuracy of predictions for recommendations. The newly developed recommendation system uses several algorithms and dynamically selects the most accurate algorithm. The system takes state-of-the-art algorithms and newly developed collaborative-filtering algorithms into account. The research work of this thesis proves that a dynamic selection of the most accurate filtering algorithm by considering more algorithms is able to increase the accuracy of the predictions significantly. This item ships from La Vergne,TN.
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A dynamic multi-algorithm collaborative-filtering system
~EN NW ABISBN: 9783659399619 bzw. 3659399612, vermutlich in Englisch, neu, Hörbuch.
Lieferung aus: Österreich, Lieferzeit: 5 Tage, zzgl. Versandkosten.
Nowadays users have access to an immense number of media content. They are able to consume thousands of TV channels and millions of video clips from online portals like YouTube. Due to the immense number of available content, users can have the problem to find content of interest. Recommendation systems are able to filter the immense number of recommendations and they are able to recommend content which fits to the interests of users. However, this research work presents a newly developed recommendation system which is able to increase the accuracy of predictions for recommendations. The newly developed recommendation system uses several algorithms and dynamically selects the most accurate algorithm. The system takes state-of-the-art algorithms and newly developed collaborative-filtering algorithms into account. The research work of this thesis proves that a dynamic selection of the most accurate filtering algorithm by considering more algorithms is able to increase the accuracy of the predictions significantly.
Nowadays users have access to an immense number of media content. They are able to consume thousands of TV channels and millions of video clips from online portals like YouTube. Due to the immense number of available content, users can have the problem to find content of interest. Recommendation systems are able to filter the immense number of recommendations and they are able to recommend content which fits to the interests of users. However, this research work presents a newly developed recommendation system which is able to increase the accuracy of predictions for recommendations. The newly developed recommendation system uses several algorithms and dynamically selects the most accurate algorithm. The system takes state-of-the-art algorithms and newly developed collaborative-filtering algorithms into account. The research work of this thesis proves that a dynamic selection of the most accurate filtering algorithm by considering more algorithms is able to increase the accuracy of the predictions significantly.
6
A dynamic multi-algorithm collaborative-filtering system
~EN PB NWISBN: 9783659399619 bzw. 3659399612, vermutlich in Englisch, LAP Lambert Academic Publishing, Taschenbuch, neu.
Lieferung aus: Deutschland, Versandkostenfrei.
A dynamic multi-algorithm collaborative-filtering system: Nowadays users have access to an immense number of media content. They are able to consume thousands of TV channels and millions of video clips from online portals like YouTube. Due to the immense number of available content, users can have the problem to find content of interest. Recommendation systems are able to filter the immense number of recommendations and they are able to recommend content which fits to the interests of users. However, this research work presents a newly developed recommendation system which is able to increase the accuracy of predictions for recommendations. The newly developed recommendation system uses several algorithms and dynamically selects the most accurate algorithm. The system takes state-of-the-art algorithms and newly developed collaborative-filtering algorithms into account. The research work of this thesis proves that a dynamic selection of the most accurate filtering algorithm by considering more algorithms is able to increase the accuracy of the predictions significantly. Englisch, Taschenbuch.
A dynamic multi-algorithm collaborative-filtering system: Nowadays users have access to an immense number of media content. They are able to consume thousands of TV channels and millions of video clips from online portals like YouTube. Due to the immense number of available content, users can have the problem to find content of interest. Recommendation systems are able to filter the immense number of recommendations and they are able to recommend content which fits to the interests of users. However, this research work presents a newly developed recommendation system which is able to increase the accuracy of predictions for recommendations. The newly developed recommendation system uses several algorithms and dynamically selects the most accurate algorithm. The system takes state-of-the-art algorithms and newly developed collaborative-filtering algorithms into account. The research work of this thesis proves that a dynamic selection of the most accurate filtering algorithm by considering more algorithms is able to increase the accuracy of the predictions significantly. Englisch, Taschenbuch.
8
A dynamic multi-algorithm collaborative-filtering system
~EN PB NWISBN: 9783659399619 bzw. 3659399612, vermutlich in Englisch, Taschenbuch, neu.
Lieferung aus: Deutschland, Next Day, Versandkostenfrei.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
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