Social Media Analytics for User Behavior Modeling: A Task Heterogeneity Perspective
Arun Reddy Nelakurthi, Jingrui HeIn 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.
年:
2020
出版:
1
出版社:
CRC Press
语言:
english
页:
114
ISBN 10:
0367211580
ISBN 13:
9780367211585
系列:
Data-Enabled Engineering
文件:
PDF, 7.53 MB
IPFS:
,
english, 2020