Social Media Analytics for User Behavior Modeling: A Task Heterogeneity Perspective

Social Media Analytics for User Behavior Modeling: A Task Heterogeneity Perspective

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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