<p><p></p><p>This SpringerBrief presents a typical life-cycle of mobile data mining applications, including:</p><p></p><ul><li>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<br></li><
Data Mining Mobile Devices
โ Scribed by Jesus Mena
- Publisher
- Auerbach Publications,CRC Press
- Year
- 2013
- Tongue
- English
- Leaves
- 317
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
With todayโs consumers spending more time on their mobiles than on their PCs, new methods of empirical stochastic modeling have emerged that can provide marketers with detailed information about the products, content, and services their customers desire.
Data Mining Mobile Devices defines the collection of machine-sensed environmental data pertaining to human social behavior. It explains how the integration of data mining and machine learning can enable the modeling of conversation context, proximity sensing, and geospatial location throughout large communities of mobile users.
- Examines the construction and leveraging of mobile sites
- Describes how to use mobile apps to gather key data about consumersโ behavior and preferences
- Discusses mobile mobs, which can be differentiated as distinct marketplacesโincluding Appleยฎ, Googleยฎ, Facebookยฎ, Amazonยฎ, and Twitterยฎ
- Provides detailed coverage of mobile analytics via clustering, text, and classification AI software and techniques
Mobile devices serve as detailed diaries of a person, continuously and intimately broadcasting where, how, when, and what products, services, and content your consumers desire. The future is mobileโdata mining starts and stops in consumers' pockets.
Describing how to analyze Wi-Fi and GPS data from websites and apps, the book explains how to model mined data through the use of artificial intelligence software. It also discusses the monetization of mobile devicesโ desires and preferences that can lead to the triangulated marketing of content, products, or services to billions of consumersโin a relevant, anonymous, and personal manner.
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<p><span>Handbook of Mobility Data Mining: Volume Three: Mobility Data-Driven Applications</span><span> introduces the fundamental technologies of mobile big data mining (MDM), advanced AI methods, and upper-level applications, helping readers comprehensively understand MDM with a bottom-up approach