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RE-RANKING RESULTS FROM SEMANTIC NATURAL LANGUAGE PROCESSING MACHINE LEARNING ALGORITHMS FOR IMPLEMENTATION IN VIDEO GAMES
RE-RANKING RESULTS FROM SEMANTIC NATURAL LANGUAGE PROCESSING MACHINE LEARNING ALGORITHMS FOR IMPLEMENTATION IN VIDEO GAMES
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机译：从语义自然语言处理机器学习算法重新排序结果，用于在视频游戏中实现
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摘要
Program code representing a semantic natural language processing (NLP) machine learning (ML) algorithm is stored in a memory. A processor executes the semantic NLP ML algorithm to generate initial scores that represent a degree of matching between candidate responses and an input phrase provided by a user during execution of program code. The processor also modifies one or more of the initial scores using one or more rules that associate a first phrase with a second phrase. The one or more rules are selected to modify the initial scores based on semantic similarity of the user input phrase and the first phrase determined by the semantic NLP ML algorithm and the semantic similarity of the response phrase with a corresponding candidate response. Execution of the program code is modified based on the modified initial scores. In some cases, the semantic NLP ML algorithm is used to implement a video game.
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