Workshop of the Cross-Language Evaluation Forum for European Languages

CLEF 2008: Evaluating Systems for Multilingual and Multimodal Information Access pp 923-926

DCU at VideoClef 2008

  • Eamonn Newman
  • Gareth J. F. Jones
Conference paper

DOI: 10.1007/978-3-642-04447-2_121

Volume 5706 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Newman E., Jones G.J.F. (2009) DCU at VideoClef 2008. In: Peters C. et al. (eds) Evaluating Systems for Multilingual and Multimodal Information Access. CLEF 2008. Lecture Notes in Computer Science, vol 5706. Springer, Berlin, Heidelberg

Abstract

We describe a baseline system for the VideoCLEF Vid2RSS task in which videos are to be classified into thematic categories based on their content. The system uses an off-the-shelf Information Retrieval system. Speech transcripts generated using automated speech recognition are indexed using default stemming and stopping methods. The categories are populated by using the category theme (or label) as a query on the collection, and assigning the retrieved items to that particular category. Run 4 of our system achieved the highest f-score in the task by maximising recall. We discuss this in terms of the primary aims of the task, i.e., automating video classification.

Keywords

Classification Information Retrieval Automatic Speech Recognition 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Eamonn Newman
    • 1
  • Gareth J. F. Jones
    • 1
  1. 1.Centre for Digital Video ProcessingDublin City UniversityDublin 9Ireland