Mobile Data Mining
Language: English
Published by Springer, Springer International Publishing Nov 2018, 2018
Series: Book 280 of 322 - SpringerBriefs in Computer Science
- Softcover
- New
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000
AbeBooks seller since January 23, 2017
Condition: New
£ 47.26
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Add to basketItem description from seller
This item is printed on demand - Print on Demand Titel. 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 KG, Sachsenplatz 4-6, 1201 Wien 68 pp. Englisch.…
Seller Inventory # 9783030021009
- Title
- Mobile Data Mining
- Author
- Yuan Yao
- Publisher
- Springer, Springer International Publishing Nov 2018
- Publication year
- 2018
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 3030021009
- ISBN 13
- 9783030021009
- Item weight
- 134 grams
- Dimensions
- 235x155x4 mm
- Series
- Book 280 of 322: SpringerBriefs in Computer Science
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.
"Synopsis" may belong to another edition of this title.
buchversandmimpf2000
Emtmannsberg, BAYE, Germany
AbeBooks seller since January 23, 2017
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