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In recent digital library systems or World Wide Web environment, many documents are beginning to be provided in the structured format, tagged in mark up languages like SGML or XML. Hence, indexing and query evaluation of structured documents have been drawing attention since they enable to access and retrieve a certain part of documents easily. However,(More)
In this article we propose a method for constructing, from raw Chinese text, a statistics-based automatic dictionary. The method makes use of local statistical information (i.e., data within a document) to identify and discard repeated string patterns, which, at an earlier stage, were substrings of legitimate words. Global statistical information (which(More)
Many natural language processing systems are being applied to clinical text, yet clinically useful results are obtained only by honing a system to a particular context. We suggest that concentration on the information needed for this processing is crucial and present a knowledge intensive methodology for mapping clinical text to LOINC. The system takes(More)
Explosion of disaster health information results in information overload among response professionals. The objective of this project was to determine the feasibility of applying semantic natural language processing (NLP) technology to addressing this overload. The project characterizes concepts and relationships commonly used in disaster health-related(More)
We investigated the dictionary-based query translation method combining the translation disambiguation process using statistic cooccurrence information trained from the provided corpus. We believe that neighboring words tend to be related in contextual meaning and have higher chance of co-occurrence particularly if adjacent words (two or more) compose a(More)
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