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"You Tube and I Find" - personalizing multimedia content access

Venkatesh, Svetha, Adams, Brett, Phung, Dinh, Dorai, Chitra, Farrell, Robert G., Agnihotri, Lalitha and Dimitrova, Nevenka 2008, "You Tube and I Find" - personalizing multimedia content access, Proceedings of the IEEE, vol. 96, no. 4, pp. 697-711, doi: 10.1109/JPROC.2008.916378.

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Title "You Tube and I Find" - personalizing multimedia content access
Author(s) Venkatesh, SvethaORCID iD for Venkatesh, Svetha
Adams, Brett
Phung, DinhORCID iD for Phung, Dinh
Dorai, Chitra
Farrell, Robert G.
Agnihotri, Lalitha
Dimitrova, Nevenka
Journal name Proceedings of the IEEE
Volume number 96
Issue number 4
Start page 697
End page 711
Total pages 15
Publisher IEEE
Place of publication Piscataway, N. J.
Publication date 2008-04
ISSN 0018-9219
Keyword(s) Information retrieval
multimedia analysis
user modeling
Summary Recent growth in broadband access and proliferation of small personal devices that capture images and videos has led to explosive growth of multimedia content available everywhereVfrom personal disks to the Web. While digital media capture and upload has become nearly universal with newer device technology, there is still a need for better tools and technologies to search large collections of multimedia data and to find and deliver the right content to a user according to her current needs and preferences. A renewed focus on the subjective dimension in the multimedia lifecycle, fromcreation, distribution, to delivery and consumption, is required to address this need beyond what is feasible today. Integration of the subjective aspects of the media itselfVits affective, perceptual, and physiological potential (both intended and achieved), together with those of the users themselves will allow for personalizing the content access, beyond today’s facility. This integration, transforming the traditional multimedia information retrieval (MIR) indexes to more effectively answer specific user needs, will allow a richer degree of personalization predicated on user intention and mode of interaction, relationship to the producer, content of the media, and their history and lifestyle. In this paper, we identify the challenges in achieving this integration, current approaches to interpreting content creation processes, to user modelling and profiling, and to personalized content selection, and we detail future directions. The structure of the paper is as follows: In Section I, we introduce the problem and present some definitions. In Section II, we present a review of the aspects of personalized content and current approaches for the same. Section III discusses the problem of obtaining metadata that is required for personalized media creation and present eMediate as a case study of an integrated media capture environment. Section IV presents the MAGIC system as a case study of capturing effective descriptive data and putting users first in distributed learning delivery. The aspects of modelling the user are presented as a case study in using user’s personality as a way to personalize summaries in Section V. Finally, Section VI concludes the paper with a discussion on the emerging challenges and the open problems.
Notes This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
Language eng
DOI 10.1109/JPROC.2008.916378
Field of Research 089999 Information and Computing Sciences not elsewhere classified
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category C2.1 Other contribution to refereed journal
Copyright notice ©2008, IEEE
Free to Read? Yes
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Document type: Journal Article
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