Abstract
This paper describes experiments we conducted in conjunction with the VideoCLEF 2009 classification task. In our second participation in the task we experimented with treating classification as an IR problem and used the Xtrieval framework [1] to run our experiments. We confirmed that the IR approach achieves strong results although the data set was changed. We proposed an automatic threshold to limit the number of labels per document. Query expansion performed better than the corresponding baseline experiments in terms of mean average precision. We also found that combining the ASR transcriptions and the archival metadata improved the classification performance unless query expansion was used.
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References
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Kürsten, J., Eibl, M. (2010). Video Classification as IR Task: Experiments and Observations. In: Peters, C., et al. Multilingual Information Access Evaluation II. Multimedia Experiments. CLEF 2009. Lecture Notes in Computer Science, vol 6242. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15751-6_49
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DOI: https://doi.org/10.1007/978-3-642-15751-6_49
Publisher Name: Springer, Berlin, Heidelberg
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