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Finding new news: novelty detection in broadcast news

Gaughan, Georgina and Smeaton, Alan F. orcid logoORCID: 0000-0003-1028-8389 (2005) Finding new news: novelty detection in broadcast news. In: AIRS 2005 - Second Asia Information Retrieval Symposium, 13-15 October 2005, Jeju Island, Korea. ISBN 978-3-540-29186-2

Abstract
The automatic detection of novelty, or newness, as part of an information retrieval system would greatly improve a searcher’s experience by presenting “documents” in order of how much extra information they add to what is already known instead of how similar they are to a user’s query. In this paper we present a novelty detection system evaluated on the AQUAINT text collection as part of our TREC 2004 Novelty Track experiments. Subsequent to participation in TREC, the algorithm has been evaluated on another collection with its parameters optimized and we present those results here. We also discuss how we are extending the text-only approach to novelty detection to also include input from video analysis.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Additional Information:The original publication is available at www.springerlink.com
Uncontrolled Keywords:novelty detection system;
Subjects:Computer Science > Digital video
Computer Science > Information retrieval
DCU Faculties and Centres:Research Initiatives and Centres > Centre for Digital Video Processing (CDVP)
Research Initiatives and Centres > Adaptive Information Cluster (AIC)
Published in: Information Retrieval Technology. Lecture Notes in Computer Science 3689. Springer Berlin / Heidelberg. ISBN 978-3-540-29186-2
Publisher:Springer Berlin / Heidelberg
Official URL:http://dx.doi.org/10.1007/11562382_54
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Irish Research Council for Science Engineering and Technology, Science Foundation Ireland, SFI 03/IN.3/I361
ID Code:262
Deposited On:10 Mar 2008 by DORAS Administrator . Last Modified 08 Nov 2018 10:46
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