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Social media analytics for user behavior modeling a task heterogeneity perspective

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서명/저자사항Social media analytics for user behavior modeling : a task heterogeneity perspective/ Arun Reddy Nelakurthi, Jingrui He.
개인저자Nelakurthi, Arun Reddy,author.
He, Jingrui,author,
형태사항1 online resource (xv, 97 pages): illustrations.
총서사항Data-enabled engineering
기타형태 저록Print version: 9781000025408
Print version: 0367211580 9780367211585
ISBN9781000025408
1000025403
9781000025361
1000025365
9780429270352
0429270356


기타표준부호10.1201/9780429270352doi
서지주기Includes bibliographical references and index.
요약In 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.
일반주제명Machine learning.
Data mining.
Social media.
Social networks.
COMPUTERS --Computer Vision & Pattern Recognition.
COMPUTERS --Data Processing --General.
COMPUTERS --Database Management --Data Mining.
Data mining.
Machine learning.
Social media.
Social networks.
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