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Evaluating Crowd Sourced Information Using Crowd Sourced Metadata

机译:使用众包元数据评估众包信息

摘要

An approach is provided for utilizing crowd sourced data to score, or weigh, candidate answers in a question/answer (QA) system. In the approach, a question is received from a user and the system identifies question keywords and a context in the question using natural language processing (NLP). The system mines crowd sourced data sets for crowd sourced information, the mining being based on the identified question keywords and context. The crowd sourced data sets have stored therein a collective opinion of a crowd of individuals. The system evaluates the mined crowd sourced information based on crowd sourced metadata. The evaluation results in a most likely answer that is returned to the user, with the most likely answer that incorporating a portion of the crowd sourced information.
机译:提供了一种利用众包数据对问题/答案(QA)系统中的候选答案进行评分或加权的方法。在该方法中,从用户接收问题,并且系统使用自然语言处理(NLP)识别问题关键字和问题中的上下文。该系统挖掘人群源数据集以获取人群源信息,该挖掘基于已识别的问题关键字和上下文。人群来源的数据集已在其中存储了人群的集体意见。该系统基于来自人群的元数据评估开采的来自人群的信息。评估结果是最有可能的答案返回给用户,最有可能的答案包含了一部分人群来源信息。

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