Chancellery Research - Research Publications
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ItemAccurate discovery of co-derivative documents via duplicate text detection(PERGAMON-ELSEVIER SCIENCE LTD, 2006-11)
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ItemCompact features for detection of near-duplicates in distributed retrieval(SPRINGER-VERLAG BERLIN, 2006)
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ItemEfficient online index maintenance for contiguous inverted lists(ELSEVIER SCI LTD, 2006-07)
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ItemDetection of video sequences using compact signatures(ASSOC COMPUTING MACHINERY, 2006-01)Digital representations are widely used for audiovisual content, enabling the creation of large online repositories of video, allowing access such as video on demand. However, the ease of copying and distribution of digital video makes piracy a growing concern for content owners. We investigate methods for identifying coderivative video content---that is, video clips that are derived from the same original source. By using dynamic programming to identify regions of similarity in video signatures, it is possible to efficiently and accurately identify coderivatives, even when these regions constitute only a small section of the clip being searched. We propose four new methods for producing compact video signatures, based on the way in which the video changes over time. The intuition is that such properties are likely to be preserved even when the video is badly degraded. We demonstrate that these signatures are insensitive to dramatic changes in video bitrate and resolution, two parameters that are often altered when reencoding. In the presence of mild degradations, our methods can accurately identify copies of clips that are as short as 5 s within a dataset 140 min long. These methods are much faster than previously proposed techniques; using a more compact signature, this query can be completed in a few milliseconds.
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ItemEfficient query expansion with auxiliary data structures(PERGAMON-ELSEVIER SCIENCE LTD, 2006-11)
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ItemThe case of the duplicate document measurement, search, and science(SPRINGER-VERLAG BERLIN, 2006)
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ItemSample sizes for query probing in uncooperative distributed information retrieval(SPRINGER-VERLAG BERLIN, 2006)
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ItemMethodologies for evaluation of note-based music-retrieval systems(INFORMS, 2006-01-01)There have been many proposed music-retrieval systems, based on a variety of principles. How the effectiveness of these systems compares is not clear. The evaluation of some systems has been informal, without the rigor applied in other areas of information retrieval, and comparison of systems is difficult because of the lack of a common data set, queries, or relevance judgments. In this paper we explain how we collected artificial and expert music queries and name-based relevance judgments, and describe software we developed for collection of manual relevance judgments. Together with a collection of downloaded musical instrument digital interface (MIDI) files, these sets of queries and relevance judgments provide valuable tools for measuring music-retrieval systems. As an example of the value of these tools, we use them to compare the effect of using the expert queries and manual judgments to that of the artificial queries and manual judgments used in our earlier experiments.