Alternative Ways for Knowledge Collection, Indexing and Robust Language Retrieval
| العنوان: | Alternative Ways for Knowledge Collection, Indexing and Robust Language Retrieval |
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| المؤلفون: | Christian Lovis, R. Baud, Anne-Marie Rassinoux, Jean-Raoul Scherrer |
| المصدر: | Methods of Information in Medicine. 37:315-326 |
| بيانات النشر: | Georg Thieme Verlag KG, 1998. |
| سنة النشر: | 1998 |
| مصطلحات موضوعية: | Advanced and Specialized Nursing, Scheme (programming language), Reflection (computer programming), Knowledge representation and reasoning, business.industry, Computer science, Search engine indexing, Health Informatics, computer.software_genre, Health Information Management, Knowledge base, Question answering, Artificial intelligence, business, computer, Natural language processing, Natural language, Sentence, computer.programming_language |
| الوصف: | Definitions are provided of the key entities in knowledge representation for Natural Language Processing (NLP). Starting from the words, which are the natural components of any sentence, both the role of expressions and the decomposition of words into their parts are emphasized. This leads to the notion of concepts, which are either primitive or composite depending on the model where they are created. The problem of finding the most adequate degree of granularity for a concept is studied. From this reflection on basic Natural Language Processing components, four categories of linguistic knowledge are recognized, that are considered to be the building blocks of a Medical Linguistic Knowledge Base (MLKB). Following on the tracks of a recent experience in building a natural language-based patient encoding browser, a robust method for conceptual indexing and query of medical texts is presented with particular attention to the scheme of knowledge representation. |
| تدمد: | 2511-705X 0026-1270 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_________::777c379b8661b37daab0a4845b432400 https://doi.org/10.1055/s-0038-1634563 |
| رقم الأكسشن: | edsair.doi...........777c379b8661b37daab0a4845b432400 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 2511705X 00261270 |
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