Titlebook: Natural Language Processing and Text Mining; Anne Kao,Stephen R. Poteet Book 2007 Springer-Verlag London 2007 Matching.Processing.Signatur

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Anne Kao,Stephen R. PoteetWhile there are a large number of books on Natural Language Processing (NLP) and several on Text Mining, there are almost none that discuss them together in any depth. This book not only discusses app

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Mining Diagnostic Text Reports by Learning to Annotate Knowledge Roles,ment level, making use of the so-called bag-of-words model. Other tasks, like document summarization, information extraction, or question answering, have to operate on the sentence level, in order to fulfill their specific requirements. While both groups of text mining tasks are typically affected b

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A Case Study in Natural Language Based Web Search, of scalability and usability of natural language approaches to search. Our solution is based on InFact?, a natural language search engine that combines the speed of keyword search with the power of natural language processing. InFact performs clause level indexing, and offers a full spectrum of fun

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Textual Signatures: Identifying Text-Types Using Latent Semantic Analysis to Measure the Cohesion oinformation that co-refers across sentences and paragraphs [.]; texts contain relations between phrases, clauses, and sentences that are often causally linked [.], [.], [.]; and texts that depend on relating a series of chronological events contain temporal features that help the reader to build a c