Data Mining Mobile Devices

With today's 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 consumers' behavior and preferences
• Discusses mobile mobs, which can be differentiated as distinct marketplaces--including Apple(R), Google(R), Facebook(R), Amazon(R), and Twitter(R)
• 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 mobile--data 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 devices' desires and preferences that can lead to the triangulated marketing of content, products, or services to billions of consumers--in a relevant, anonymous, and personal manner.