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GENERATING, USING A MACHINE LEARNING MODEL, REQUEST AGNOSTIC INTERACTION SCORES FOR ELECTRONIC COMMUNICATIONS, AND UTILIZATION OF SAME
GENERATING, USING A MACHINE LEARNING MODEL, REQUEST AGNOSTIC INTERACTION SCORES FOR ELECTRONIC COMMUNICATIONS, AND UTILIZATION OF SAME
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机译：生成，使用机器学习模型，请求电子通信的非电子相互作用分数以及相同的利用
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摘要
Training and/or utilizing a machine learning model to generate request agnostic predicted interaction scores for electronic communications, and to utilization of request agnostic predicted interaction scores in determining whether, and/or how, to provide corresponding electronic communications to a client device in response to a request. A request agnostic predicted interaction score for an electronic communication provides an indication of quality of the communication, and is generated independent of corresponding request(s) for which it is utilized. In many implementations, a request agnostic predicted interaction score for an electronic communication is generated "offline" relative to corresponding request(s) for which it is utilized, and is pre-indexed with (or otherwise assigned to) the electronic communication. This enables fast and efficient retrieval, and utilization, of the request agnostic interaction score by computing device(s), when the electronic communication is responsive to a request.
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