988 resultados para Automatic Visual Word Dictionary Calculation


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In this paper, we propose an unsupervised methodology to automatically discover pairs of semantically related words by highlighting their local environment and evaluating their semantic similarity in local and global semantic spaces. This proposal di®ers from previous research as it tries to take the best of two different methodologies i.e. semantic space models and information extraction models. It can be applied to extract close semantic relations, it limits the search space and it is unsupervised.

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While multimedia data, image data in particular, is an integral part of most websites and web documents, our quest for information so far is still restricted to text based search. To explore the World Wide Web more effectively, especially its rich repository of truly multimedia information, we are facing a number of challenging problems. Firstly, we face the ambiguous and highly subjective nature of defining image semantics and similarity. Secondly, multimedia data could come from highly diversified sources, as a result of automatic image capturing and generation processes. Finally, multimedia information exists in decentralised sources over the Web, making it difficult to use conventional content-based image retrieval (CBIR) techniques for effective and efficient search. In this special issue, we present a collection of five papers on visual and multimedia information management and retrieval topics, addressing some aspects of these challenges. These papers have been selected from the conference proceedings (Kluwer Academic Publishers, ISBN: 1-4020- 7060-8) of the Sixth IFIP 2.6 Working Conference on Visual Database Systems (VDB6), held in Brisbane, Australia, on 29–31 May 2002.

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Groups of Grade 3 children were tested on measures of word-level literacy and undertook tasks that required the ability to associate sounds with letter sequences and that involved visual, auditory and phonological-processing skills. These groups came from different language backgrounds in which the language of instruction was Arabic, Chinese, English, Hungarian or Portuguese. Similar measures were used across the groups, with tests being adapted to be appropriate for the language of the children. Findings indicated that measures of decoding and phonological-processing skills were good predictors of word reading and spelling among Arabic- and English-speaking children, but were less able to predict variability in these same early literacy skills among Chinese- and Hungarian-speaking children, and were better at predicting variability in Portuguese word reading than spelling. Results were discussed with reference to the relative transparency of the script and issues of dyslexia assessment across languages. Overall, the findings argue for the need to take account of features of the orthography used to represent a language when developing assessment procedures for a particular language and that assessment of word-level literacy skills and a phonological perspective of dyslexia may not be universally applicable across all language contexts. Copyright (C) 2008 John Wiley & Sons, Ltd.