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An investigation into feature effectiveness for multimedia hyperlinking

Chen, Shu, Eskevich, Maria orcid logoORCID: 0000-0002-1242-0753, Jones, Gareth J.F. orcid logoORCID: 0000-0003-2923-8365 and O'Connor, Noel E. orcid logoORCID: 0000-0002-4033-9135 (2014) An investigation into feature effectiveness for multimedia hyperlinking. In: The 20th Anniversary International Conference on MultiMedia Modeling (MMM 2014), 6-10 Jan 2014, Dublin, Ireland.

Abstract
The increasing amount of archival multimedia content available online is creating increasing opportunities for users who are interested in exploratory search behaviour such as browsing. The user experience with online collections could therefore be improved by enabling navigation and recommendation within multimedia archives, which can be supported by allowing a user to follow a set of hyperlinks created within or across documents. The main goal of this study is to compare the performance of dierent multimedia features for automatic hyperlink generation. In our work we construct multimedia hyperlinks by indexing and searching textual and visual features extracted from the blip.tv dataset. A user-driven evaluation strategy is then proposed by applying the Amazon Mechanical Turk (AMT) crowdsourcing platform, since we believe that AMT workers represent a good example of "real world" users. We conclude that textual features exhibit better performance than visual features for multimedia hyperlink construction. In general, a combination of ASR transcripts and metadata provides the best results.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:Multimedia; Hyperlinking; Crowdsourcing; Information Retrieval
Subjects:Computer Science > Multimedia systems
Computer Science > Information retrieval
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering
Research Initiatives and Centres > Centre for Next Generation Localisation (CNGL)
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Initiatives and Centres > CLARITY: The Centre for Sensor Web Technologies
Published in: Proceedings of MMM 2014. .
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Science, European Framework Programme 7
ID Code:20387
Deposited On:22 Jan 2015 10:52 by Gareth Jones . Last Modified 10 Oct 2018 09:21
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