102,39 €
Nelakurthi, A: Social Media Analytics for User Behavior Mode
Nelakurthi, A: Social Media Analytics for User Behavior Mode
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Nelakurthi, A: Social Media Analytics for User Behavior Mode
Nelakurthi, A: Social Media Analytics for User Behavior Mode
El. knyga:
102,39 €
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 e…
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Aprašymas

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.

102,39 €
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Mažiausia kaina užfiksuota: 2025-07-20 06:43:50


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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