Articles liés à Mobile Data Mining
Synopsis
This SpringerBrief presents a typical life-cycle of mobile data mining applications, including:
- data capturing and processing which determines what data to collect, how to collect these data, and how to reduce the noise in the data based on smartphone sensors
- feature engineering which extracts and selects features to serve as the input of algorithms based on the collected and processed data
- model and algorithm design
Energy saving is a fundamental requirement of mobile applications, due to the limited battery capacity of smartphones. The authors explore the existing practices in the methodology level (e.g. by designing hierarchical models) for saving energy. Another fundamental requirement of mobile applications is personalization. Most of the existing methods tend to train generic models for all users, but the authors provide existing personalized treatments for mobile applications, as the behaviors may differ greatly from one user to another in many mobile applications. The third requirement is real-time. That is, the mobile application should return responses in a real-time manner, meanwhile balancing effectiveness and efficiency.
This SpringerBrief targets data mining and machine learning researchers and practitioners working in these related fields. Advanced level students studying computer science and electrical engineering will also find this brief useful as a study guide.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
- ÉditeurSpringer
- Date d'édition2018
- ISBN 10 3030021009
- ISBN 13 9783030021009
- ReliureBroché
- Langueanglais
- Nombre de pages68
- Coordonnées du fabricantnon disponible
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Mobile Data Mining
Edité par
Springer International Publishing, 2018
ISBN 10 : 3030021009
ISBN 13 : 9783030021009
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Couverture souple
Vendeur : Buchpark, Trebbin, Allemagne
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Etat : Sehr gut. Zustand: Sehr gut | Seiten: 68 | Sprache: Englisch | Produktart: Bücher. N° de réf. du vendeur 29189940/2
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Mobile Data Mining
Edité par
Springer International Publishing, 2018
ISBN 10 : 3030021009
ISBN 13 : 9783030021009
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Couverture souple
Vendeur : moluna, Greven, Allemagne
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This SpringerBrief presents a typical life-cycle of mobile data mining applications, including:data capturing and processing which determines what data to collect, how to collect these data, and how to reduce the noise. N° de réf. du vendeur 244074874
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Mobile Data Mining
Edité par
Springer International Publishing, 2018
ISBN 10 : 3030021009
ISBN 13 : 9783030021009
Neuf
Taschenbuch
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This SpringerBrief presents a typical life-cycle of mobile data mining applications,including:data capturing and processing which determines what data tocollect, how to collect these data, and how to reduce the noise in the databased on smartphone sensorsfeature engineering which extracts andselects features to serve as the input of algorithms based on the collectedand processed datamodel and algorithm designIn particular, this brief concentrateson the model and algorithm design aspect, and explains three challenging requirementsof mobile data mining applications: energy-saving, personalization, and real-timeEnergy saving is a fundamental requirement of mobile applications, due to thelimited battery capacity of smartphones. The authors explore the existingpractices in the methodology level (e.g. by designing hierarchical models) for saving energy. Another fundamental requirement of mobileapplications is personalization. Most of the existing methods tend to train generic models for all users, but the authors provide existing personalizedtreatments for mobile applications, as the behaviors may differ greatly fromone user to another in many mobile applications. The third requirement isreal-time. That is, the mobile application should return responses in a real-timemanner, meanwhile balancing effectiveness and efficiency.This SpringerBrief targets data mining and machine learning researchers and practitionersworking in these related fields. Advanced level students studying computer scienceand electrical engineering will also find this brief useful as a study guide. N° de réf. du vendeur 9783030021009
Quantité disponible : 1 disponible(s)
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Mobile Data Mining
Edité par
Springer International Publishing Nov 2018, 2018
ISBN 10 : 3030021009
ISBN 13 : 9783030021009
Neuf
Taschenbuch
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This SpringerBrief presents a typical life-cycle of mobile data mining applications,including:data capturing and processing which determines what data tocollect, how to collect these data, and how to reduce the noise in the databased on smartphone sensorsfeature engineering which extracts andselects features to serve as the input of algorithms based on the collectedand processed datamodel and algorithm designIn particular, this brief concentrateson the model and algorithm design aspect, and explains three challenging requirementsof mobile data mining applications: energy-saving, personalization, and real-timeEnergy saving is a fundamental requirement of mobile applications, due to thelimited battery capacity of smartphones. The authors explore the existingpractices in the methodology level (e.g. by designing hierarchical models) for saving energy. Another fundamental requirement of mobileapplications is personalization. Most of the existing methods tend to train generic models for all users, but the authors provide existing personalizedtreatments for mobile applications, as the behaviors may differ greatly fromone user to another in many mobile applications. The third requirement isreal-time. That is, the mobile application should return responses in a real-timemanner, meanwhile balancing effectiveness and efficiency.This SpringerBrief targets data mining and machine learning researchers and practitionersworking in these related fields. Advanced level students studying computer scienceand electrical engineering will also find this brief useful as a study guide. 68 pp. Englisch. N° de réf. du vendeur 9783030021009
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Mobile Data Mining
ISBN 10 : 3030021009
ISBN 13 : 9783030021009
Neuf
Taschenbuch
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. Neuware -This SpringerBrief presents a typical life-cycle of mobile data mining applications, including:data capturing and processing which determines what data to collect, how to collect these data, and how to reduce the noise in the data based on smartphone sensorsfeature engineering which extracts and selects features to serve as the input of algorithms based on the collected and processed datamodel and algorithm designIn particular, this brief concentrates on the model and algorithm design aspect, and explains three challenging requirements of mobile data mining applications: energy-saving, personalization, and real-timeEnergy saving is a fundamental requirement of mobile applications, due to the limited battery capacity of smartphones. The authors explore the existing practices in the methodology level (e.g. by designing hierarchical models) for saving energy. Another fundamental requirement of mobile applications is personalization. Most of the existing methods tend to train generic models for all users, but the authors provide existing personalized treatments for mobile applications, as the behaviors may differ greatly from one user to another in many mobile applications. The third requirement is real-time. That is, the mobile application should return responses in a real-time manner, meanwhile balancing effectiveness and efficiency.This SpringerBrief targets data mining and machine learning researchers and practitioners working in these related fields. Advanced level students studying computer science and electrical engineering will also find this brief useful as a study guide.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 68 pp. Englisch. N° de réf. du vendeur 9783030021009
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Mobile Data Mining
Vendeur : Revaluation Books, Exeter, Royaume-Uni
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Paperback. Etat : Brand New. 68 pages. 9.25x6.10x0.35 inches. In Stock. N° de réf. du vendeur __3030021009
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Mobile Data Mining
Vendeur : Revaluation Books, Exeter, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Paperback. Etat : Brand New. 68 pages. 9.25x6.10x0.35 inches. In Stock. N° de réf. du vendeur 3030021009
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Mobile Data Mining (SpringerBriefs in Computer Science)
Vendeur : dsmbooks, Liverpool, Royaume-Uni
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Paperback. Etat : New. New. book. N° de réf. du vendeur D8F0-0-M-3030021009-6
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