SOCIAL MEDIA ANALYTICS FOR USER BEHAVIOR MODELING [electronic resource] : a task heterogeneity perspective.
By: Nelakurthi, Arun Reddy
.
Contributor(s): He, Jingrui.
Material type: 
BookSeries: Publisher: Boca Raton : CRC Press, 2020Description: 1 online resource.ISBN: 9781000025408; 1000025403; 9780429270352; 0429270356; 9781000025361; 1000025365.Subject(s): Machine learning | Data mining | Social media | Social networks | COMPUTERS / Computer Vision & Pattern Recognition | COMPUTERS / Data Processing / General | COMPUTERS / Database Management / Data MiningDDC classification: 006.312 Online resources: Taylor & Francis | OCLC metadata license agreement Summary: 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.
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.
OCLC-licensed vendor bibliographic record.
There are no comments for this item.