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Selection and ranking of text from highly imperfect transcripts for retrieval of video content

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SIGIR '07: Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval

Pages 791 - 792

https://doi.org/10.1145/1277741.1277911

Published: 23 July 2007 Publication History

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Abstract

In the domain of video content retrieval, we present an approach for selecting words and phrases from highly imperfect automatically generated transcripts. Extracted terms are ranked according to their descriptiveness and presented to the user in a multimedia browser interface. We use sense querying from the WordNet lexical database for our method of text selection and ranking. Evaluation of 679 video summarization tasks from 442 users shows that the method of ranking and emphasizing terms according to descriptiveness results in higher accuracy responses in less time compared to the baseline of no ranking.

References

[1]

Campbell, M., Haubold, A., Ebadollahi, S., Naphade, M.R., Natsev, P., Smith, J.R., Tesic, J., and Xie, L. IBM Research TRECVID-2006 Video Retrieval System. Proc. TRECVID 2006 Workshop. NIST Special Publications, 2006.

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[2]

Haubold, A., and Kender, J.R. Analysis and Visualization of Index Words from Audio Transcripts of Instructional Videos. MCBAR '04. IEEE Press, New York, NY, 2004, 570--573.

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[3]

http://wordnet.princeton.edu

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[4]

http://www.aquaphoenix.com/research/vastmm

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Haubold ADutta PKender JEL Saddik AVuong SGriwodz CDel Bimbo ACandan KJaimes A(2008)Evaluation of video browser features and user interaction with VAST MMProceedings of the 16th ACM international conference on Multimedia10.1145/1459359.1459419(449-458)Online publication date: 26-Oct-2008
https://dl.acm.org/doi/10.1145/1459359.1459419
Haubold AKender JSebe NWorring M(2007)VAST MMProceedings of the 6th ACM international conference on Image and video retrieval10.1145/1282280.1282286(41-48)Online publication date: 9-Jul-2007
https://dl.acm.org/doi/10.1145/1282280.1282286

Index Terms

Selection and ranking of text from highly imperfect transcripts for retrieval of video content
1. Information systems
  1. Information retrieval
    1. Retrieval models and ranking
    2. Retrieval tasks and goals
      1. Document filtering
      2. Information extraction

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Published In

SIGIR '07: Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval

July 2007

946 pages

ISBN:9781595935977

DOI:10.1145/1277741

General Chairs:
Wessel Kraaij
TNO, The Netherlands
,
Arjen P. de Vries
CWI, The Netherlands
,
Program Chairs:
Charles L. A. Clarke
University of Waterloo, Canada
,
Norbert Fuhr
University of Duisburg-Essen, Germany
,
Noriko Kando
National Institute of Informatics, Japan

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 23 July 2007

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SIGIR07: The 30th Annual International SIGIR Conference

July 23 - 27, 2007

Amsterdam, The Netherlands

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Overall Acceptance Rate 792 of 3,983 submissions, 20%

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Haubold ADutta PKender JEL Saddik AVuong SGriwodz CDel Bimbo ACandan KJaimes A(2008)Evaluation of video browser features and user interaction with VAST MMProceedings of the 16th ACM international conference on Multimedia10.1145/1459359.1459419(449-458)Online publication date: 26-Oct-2008
https://dl.acm.org/doi/10.1145/1459359.1459419
Haubold AKender JSebe NWorring M(2007)VAST MMProceedings of the 6th ACM international conference on Image and video retrieval10.1145/1282280.1282286(41-48)Online publication date: 9-Jul-2007
https://dl.acm.org/doi/10.1145/1282280.1282286

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Ranking web sites using domain ontology concepts

Re-ranking search results using query logs

Content and link-structure perspective of ranking webpages: A review

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