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.
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