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PREDICTION-MODEL-BASED MAPPING AND/OR SEARCH USING A MULTI-DATA-TYPE VECTOR SPACE

机译:使用多数据类型矢量空间的基于预测模型的映射和/或搜索

摘要

In certain embodiments, content items may be obtained, where each of the content items may include multiple data types. Machine learning models may be caused to be trained based on the content items to map data in a vector space by providing at least a first portion of each of the content items as input to at least one of the machine learning models and providing at least a second portion of each of the content items as input to at least another one of the machine learning models. A search request for results may be obtained, where the search request includes search parameters. One or more locations within the vector space may be predicted (e.g., by one or more of the machine learning models) based on the search parameters. Information (indicating content items mapped to or proximate the predicted locations) may be provided as a request response.
机译:在某些实施例中,可以获得内容项,其中每个内容项可以包括多种数据类型。通过提供每个内容项的至少第一部分作为对至少一个机器学习模型的输入,可以使得基于内容项对机器学习模型进行训练以在矢量空间中映射数据。每个内容项的第二部分作为对至少另一个机器学习模型的输入。可以获得针对结果的搜索请求,其中搜索请求包括搜索参数。向量空间内的一个或多个位置可以基于搜索参数来预测(例如,通过一个或多个机器学习模型)。可以提供信息(指示映射到预测位置或在预测位置附近的内容项)作为请求响应。

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