Browsing by Subject "Text retrieval"

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    Performance of query processing implementations in ranking-based text retrieval systems using inverted indices
    (Elsevier Ltd, 2006-07) Cambazoglu, B. B.; Aykanat, Cevdet
    Similarity calculations and document ranking form the computationally expensive parts of query processing in ranking-based text retrieval. In this work, for these calculations, 11 alternative implementation techniques are presented under four different categories, and their asymptotic time and space complexities are investigated. To our knowledge, six of these techniques are not discussed in any other publication before. Furthermore, analytical experiments are carried out on a 30 GB document collection to evaluate the practical performance of different implementations in terms of query processing time and space consumption. Advantages and disadvantages of each technique are illustrated under different querying scenarios, and several experiments that investigate the scalability of the implementations are presented. © 2005 Elsevier Ltd. All rights reserved.
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    What's news, what's not? Associating news videos with words
    (Springer, 2004) Duygulu, P.; Hauptmann, A.
    Text retrieval from broadcast news video is unsatisfactory, because a transcript word frequently does not directly 'describe' the shot when it was spoken. Extending the retrieved region to a window around the matching keyword provides better recall, but low precision. We improve on text retrieval using the following approach: First we segment the visual stream into coherent story-like units, using a set of visual news story delimiters. After filtering out clearly irrelevant classes of shots, we are still left with an ambiguity of how words in the transcript relate to the visual content in the remaining shots of the story. Using a limited set of visual features at different semantic levels ranging from color histograms, to faces, cars, and outdoors, an association matrix captures the correlation of these visual features to specific transcript words. This matrix is then refined using an EM approach. Preliminary results show that this approach has the potential to significantly improve retrieval performance from text queries. © Springer-Verlag 2004.