NDLI: Learning in high-dimensional multimedia data: the state of the art

Content Provider	Springer Nature Link
Author	Gao, Lianli Song, Jingkuan Liu, Xingyi Shao, Junming Liu, Jiajun Shao, Jie
Copyright Year	2015
Abstract	During the last decade, the deluge of multimedia data has impacted a wide range of research areas, including multimedia retrieval, 3D tracking, database management, data mining, machine learning, social media analysis, medical imaging, and so on. Machine learning is largely involved in multimedia applications of building models for classification and regression tasks, etc., and the learning principle consists in designing the models based on the information contained in the multimedia dataset. While many paradigms exist and are widely used in the context of machine learning, most of them suffer from the ‘curse of dimensionality’, which means that some strange phenomena appears when data are represented in a high-dimensional space. Given the high dimensionality and the high complexity of multimedia data, it is important to investigate new machine learning algorithms to facilitate multimedia data analysis. To deal with the impact of high dimensionality, an intuitive way is to reduce the dimensionality. On the other hand, some researchers devoted themselves to designing some effective learning schemes for high-dimensional data. In this survey, we cover feature transformation, feature selection and feature encoding, three approaches fighting the consequences of the curse of dimensionality. Next, we briefly introduce some recent progress of effective learning algorithms. Finally, promising future trends on multimedia learning are envisaged.
Starting Page	303
Ending Page	313
Page Count	11
File Format	PDF
ISSN	09424962
Journal	Multimedia Systems
Volume Number	23
Issue Number	3
e-ISSN	14321882
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2015-10-20
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	High dimensional Multimedia data Learning Survey Multimedia Information Systems Computer Communication Networks Operating Systems Data Storage Representation Data Encryption Computer Graphics
Content Type	Text
Resource Type	Article
Subject	Computer Networks and Communications Information Systems Media Technology Hardware and Architecture Software

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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