Multimedia Recommendation: Technology and Techniques

In recent years, we have witnessed a rapid growth in the availability of digital multimedia on various application platforms and domains. Consequently, the problem of information overload has become more and more serious. In order to tackle the challenge, various multimedia recommendation technologi...

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Main Authors: SHEN, Jialie, WANG, Meng, YAN, Shuicheng, CUI, Peng
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2013
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Online Access:https://ink.library.smu.edu.sg/sis_research/1829
https://ink.library.smu.edu.sg/context/sis_research/article/2828/viewcontent/p1131_shen.pdf
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spelling sg-smu-ink.sis_research-28282018-07-13T03:18:34Z Multimedia Recommendation: Technology and Techniques SHEN, Jialie WANG, Meng YAN, Shuicheng CUI, Peng In recent years, we have witnessed a rapid growth in the availability of digital multimedia on various application platforms and domains. Consequently, the problem of information overload has become more and more serious. In order to tackle the challenge, various multimedia recommendation technologies have been developed by different research communities (e.g., multimedia systems, information retrieval, machine learning and computer version). Meanwhile, many commercial web systems (e.g., Flick, YouTube, and Last.fm) have successfully applied recommendation techniques to provide users personalized content and services in a convenient and flexible way. When looking back, the information retrieval (IR) community has a long history of studying and contributing recommender system design and related issues. It has been proven that the recommender systems can effectively assist users in handling information overload and provide high-quality personalization. While several courses were dedicated to multimedia retrieval in the recent decade, to the best of our knowledge, the tutorial is the first one specifically focusing on multimedia recommender systems and their applications on various domains and media contents. We plan to summarize the research along this direction and provide an impetus for further research on this important topic. Half-day tutorial. 2013-01-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/1829 info:doi/10.1145/2484028.2484194 https://ink.library.smu.edu.sg/context/sis_research/article/2828/viewcontent/p1131_shen.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Algorithms Performance Theory Multimedia Recommendation Databases and Information Systems Numerical Analysis and Scientific Computing
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Algorithms
Performance
Theory
Multimedia
Recommendation
Databases and Information Systems
Numerical Analysis and Scientific Computing
spellingShingle Algorithms
Performance
Theory
Multimedia
Recommendation
Databases and Information Systems
Numerical Analysis and Scientific Computing
SHEN, Jialie
WANG, Meng
YAN, Shuicheng
CUI, Peng
Multimedia Recommendation: Technology and Techniques
description In recent years, we have witnessed a rapid growth in the availability of digital multimedia on various application platforms and domains. Consequently, the problem of information overload has become more and more serious. In order to tackle the challenge, various multimedia recommendation technologies have been developed by different research communities (e.g., multimedia systems, information retrieval, machine learning and computer version). Meanwhile, many commercial web systems (e.g., Flick, YouTube, and Last.fm) have successfully applied recommendation techniques to provide users personalized content and services in a convenient and flexible way. When looking back, the information retrieval (IR) community has a long history of studying and contributing recommender system design and related issues. It has been proven that the recommender systems can effectively assist users in handling information overload and provide high-quality personalization. While several courses were dedicated to multimedia retrieval in the recent decade, to the best of our knowledge, the tutorial is the first one specifically focusing on multimedia recommender systems and their applications on various domains and media contents. We plan to summarize the research along this direction and provide an impetus for further research on this important topic. Half-day tutorial.
format text
author SHEN, Jialie
WANG, Meng
YAN, Shuicheng
CUI, Peng
author_facet SHEN, Jialie
WANG, Meng
YAN, Shuicheng
CUI, Peng
author_sort SHEN, Jialie
title Multimedia Recommendation: Technology and Techniques
title_short Multimedia Recommendation: Technology and Techniques
title_full Multimedia Recommendation: Technology and Techniques
title_fullStr Multimedia Recommendation: Technology and Techniques
title_full_unstemmed Multimedia Recommendation: Technology and Techniques
title_sort multimedia recommendation: technology and techniques
publisher Institutional Knowledge at Singapore Management University
publishDate 2013
url https://ink.library.smu.edu.sg/sis_research/1829
https://ink.library.smu.edu.sg/context/sis_research/article/2828/viewcontent/p1131_shen.pdf
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