Concluding remarks
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...
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| Main Authors: | , , |
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| Format: | text |
| Language: | English |
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Institutional Knowledge at Singapore Management University
2019
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| Online Access: | https://ink.library.smu.edu.sg/sis_research/6062 https://ink.library.smu.edu.sg/context/sis_research/article/7065/viewcontent/concluding_remarks.pdf |
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| Institution: | Singapore Management University |
| Language: | English |
| Summary: | 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. |
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