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METHOD AND SYSTEM FOR IMPROVING CONTENT SEARCHING IN A QUESTION AND ANSWER CUSTOMER SUPPORT SYSTEM BY USING A CROWD-MACHINE LEARNING HYBRID PREDICTIVE MODEL
METHOD AND SYSTEM FOR IMPROVING CONTENT SEARCHING IN A QUESTION AND ANSWER CUSTOMER SUPPORT SYSTEM BY USING A CROWD-MACHINE LEARNING HYBRID PREDICTIVE MODEL
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机译:通过使用拥挤机器学习混合预测模型改进问题和答案客户支持系统中内容搜索的方法和系统
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摘要
A method and system improves content searching in a question and answer customer support system by using a crowd-machine learning hybrid predictive model, according to one embodiment. The question and answer customer support system determines which customer support content to provide to users by using the hybrid predictive model, according to one embodiment. The question and answer customer support system receives a search query from a user and applies the search query (or a representation of the search query) to the hybrid predictive model, according to one embodiment. The hybrid predictive model generates a likelihood that particular customer support content is relevant to a user's search query, according to one embodiment. The question and answer customer support system acquires user feedback from users and updates/trains the hybrid predictive model based on the user feedback, according to one embodiment.
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