Winner of the "Outstanding Academic Title" recognition by Choice
for the 2020 OAT Awards. The Choice OAT Award represents the
highest caliber of scholarly titles that have been reviewed by
Choice and conveys the extraordinary recognition of the academic
community. In recent years social media has gained significant
popularity and has become an essential medium of communication.
Such user-generated content provides an excellent scenario for
applying the metaphor of mining any information. Transfer learning
is a research problem in machine learning that focuses on
leveraging the knowledge gained while solving one problem and
applying it to a different, but related problem. Features: Offers
novel frameworks to study user behavior and for addressing and
explaining task heterogeneity Presents a detailed study of existing
research Provides convergence and complexity analysis of the
frameworks Includes algorithms to implement the proposed research
work Covers extensive empirical analysis Social Media Analytics for
User Behavior Modeling: A Task Heterogeneity Perspective is a guide
to user behavior modeling in heterogeneous settings and is of great
use to the machine learning community.
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