基于Web内容的多语言问答自适应生成

M. Gatius
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引用次数: 1

摘要

本文描述了自适应地从web内容生成问题和答案,以帮助用户搜索信息。该方法集成了用户模型、领域受限知识表示、自然语言和包装技术。该建议基于将特定场景中涉及的主要概念表示为一组属性,并将用户模型表示为与每个用户相关的这些概念属性的子集。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。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adaptive Generation of Multilingual Questions and Answers from Web Content
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.
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