Publication Type

Book Chapter

Version

publishedVersion

Publication Date

5-2019

Abstract

This chapter summarizes the major contributions in this book and discusses their possible positions and requirements in some future scenarios. Section 8.1 follows the book structure to revisit the key contributions of this book in both theories and applications. The developed algorithms, such as the VA-ARTs for hyperparameter adaptation and the GHF-ART for multimedia representation and fusion, and the four applications, such as clustering and retrieving socially enriched multimedia data, are concentrated using one paragraph and three paragraphs, respectively. In Sect. 8.2, the roles of the proposed ART-embodied algorithms in social media clustering tasks are highlighted, and their possible evolutions using the state-of-the-art representation learning techniques to fit the increasingly rich social media data and demands are discussed.

Discipline

Databases and Information Systems | Software Engineering

Research Areas

Data Science and Engineering

Publication

Adaptive Resonance Theory in Social Media Data Clustering

First Page

175

Last Page

179

ISBN

9783030029845

Identifier

10.1007/978-3-030-02985-2_8

Publisher

Springer

City or Country

Cham

Additional URL

https://doi.org/10.1007/978-3-030-02985-2_8

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