Librería Portfolio

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.



Table of Contents
1. Introduction. 2. Related Work. 3. User-Guided Cross-Domain Sentiment Classification. 4. Similar Actor Recommendation. 5. Source-Free Domain Adaptation of the Off-the-Shelf Classifier. 6. Social Media for Diabetes Management. 7. Conclusion and Future Work.