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Titlebook: String Processing and Information Retrieval; 10th International S Mario A. Nascimento,Edleno S. Moura,Arlindo L. Oli Conference proceedings

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Bit-Parallel Approximate String Matching Algorithms with Transposition a single edit operation to insert, delete or substitute a character. Depending on the parameters of the search, currently the fastest non-filtering algorithms in practice are the .(. ⌈./. ⌉) algorithm of Wu & Manber, the .(⌈./. ⌉.) algorithm of Baeza-Yates & Navarro, and the .(⌈./. ⌉.) algorithm of
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SCM: Structural Contexts Model for Improving Compression in Semistructured Text Databasesture of the text. The idea is to use a separate semiadaptive model to compress the text that lies inside each different structure type (e.g., different XML tag). The intuition behind the idea is that the distribution of all the texts that belong to a given structure type should be similar, and diffe
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Ranking Structured Documents Using Utility Theory in the Bayesian Network Retrieval Modelthodologies is to refine a first ranking of structural units, generated by means of an Information Retrieval Model based on Bayesian Networks. Units are newly arranged in the new ranking by combining their posterior probabilities, obtained in the first stage, with the expected utility of retrieving
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An Empirical Comparison of Text Categorization Methods the Vector and Latent Semantic Analysis (LSA) methods, a classifier based on Support Vector Machines (SVM) and the k-Nearest Neighbor variations of the Vector and LSA models..We report the results obtained using the Mean Reciprocal Rank as a measure of overall performance, a commonly used evaluatio
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A Bit-Parallel Suffix Automaton Approach for (,,,)-Matching in Music Retrievalgers, find the occurrences .′ of the pattern in the text such that (.) ∀ 1 ≤ . ≤ .,  |.. − .′.| ≤ ., and (.) ∑ . |.. − .′.| ≤ .. Several techniques for (.,.)-matching have been proposed. In this paper we show that a classical string matching technique that combines bit-parallelism and suffix automat
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