MEANS : une approche sémantique pour la recherche de réponses aux questions médicales [MEANS: a semantic approach to medical question answering]
MEANS : une approche sémantique pour la recherche de réponses aux questions médicales [MEANS: a semantic approach to medical question answering]
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意思 : une approche sémantique pour la recherche de réponses aux questions médicales [意思：医学问答的语义方法]
作者：
Asma Ben Abacha;Pierre Zweigenbaum
我们提出了一种医学问答方法，称为MEANS。该方法依靠自然语言处理技术从用户问题和医学语料库中提取医学实体和关系。它还使用语义Web语言来表示和查询用户搜索的信息。该功能允许使用标准语言共享从文本语料库中提取的信息，并考虑中长期的增量知识获取。MEANS构造一个初始的SPARQL查询和几个宽松的查询，作为用户问题的语义解释。在真实数据集上对MEANS的评估显示了精度和MRR的良好结果，并显示了查询松弛技术的显着优势。
We present a medical question answering approach, called MEANS. This approach relies on natural language processing techniques to extract medical entities and relations from the user questions and medical corpora. It also uses semantic Web languages to represent and query the information searched by the users. This feature allows to share the information ex- tracted from textual corpora using standard languages and to consider incremental knowledge acquisition in mid-and-long terms. MEANS constructs an initial SPARQL query and several relaxed queries as semantic interpretations of a user question. The evaluation of MEANS on a real dataset shows promising results for both precision and MRR and showed the significant benefits of the query relaxation technique.