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Adaptive Generation of Multilingual Questions and Answers from Web Content

机译:从Web内容自适应生成多语言问答

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This article describes the adaptive generation of questions and answers from web content to assist the user when searching for information. The approach proposed integrates user models, domain-restricted knowledge representation, natural language and wrappers techniques. This proposal is based on the representation of the main concepts involved in a specific scenario as a set of attributes, and the user models as the subset of those conceptual attributes relevant for each user. The approach described has been applied to generate multilingual personalized questions and answers from web sites in two different domains: university courses and dissemination on nutrition.
机译:本文介绍了从Web内容自适应生成问题和答案的过程,以帮助用户搜索信息。提出的方法集成了用户模型,领域受限的知识表示,自然语言和包装技术。该提议基于特定场景中涉及的主要概念作为一组属性的表示,并且用户将模型建模为与每个用户相关的那些概念属性的子集。所描述的方法已应用于从两个不同领域的网站生成多语言个性化问题和答案:大学课程和营养传播。

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