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QUERY-BASED RECOMMENDATION SYSTEMS USING MACHINE LEARNING-TRAINED CLASSIFIER
QUERY-BASED RECOMMENDATION SYSTEMS USING MACHINE LEARNING-TRAINED CLASSIFIER
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机译:基于查询的推荐系统,使用机器学习培训的分类器
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摘要
Systems and methods for query-based recommendation systems using machine learning-trained classifiers are provided. A service provider server receives, from a communication device through an application programming interface, a query in an interaction between the server provider server and the communication device. The service provider server generates a vector of first latent features from a set of first visible features associated with the query using a machine learning-trained classifier. The service provider server generates a likelihood scalar value indicating a likelihood of the query is answered by a candidate user in a set of users using a combination of the vector of first latent features and a vector of second latent features. The service provider server provides, to the communication device through the application programming interface, a recommendation message as a response to the query, where the recommendation message includes the likelihood scalar value and an indication of the candidate user.
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