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System for Multi-Task Distribution Learning With Numeric-Aware Knowledge Graphs

机译:用数字感知知识图表多任务分发学习系统

摘要

This disclosure provides methods and systems for predicting missing links and previously unknown numerals in a knowledge graph. A jointly trained multi-task machine learning model is disclosed for integrating a symbolic pipeline for predicting missing links and a regression numerical pipeline for predicting numerals with prediction uncertainty. The two prediction pipelines share a jointly trained embedding space of entities and relationships of the knowledge graph. The numerical pipeline additionally includes a second-layer multi-task regression neural network containing multiple regression neural networks for parallel numerical prediction tasks with a cross stich network allowing for information/model parameter sharing between the various parallel numerical prediction tasks.
机译:本公开提供了用于预测知识图中的缺失链路和先前未知的数字的方法和系统。公开了一种共同训练的多任务机器学习模型,用于集成符号流水线,用于预测缺失链路和回归数管线,用于预测具有预测不确定性的数字。两种预测管道共享一个共同训练的嵌入空间的实体和知识图的关系。数值管线还包括包含多元回归神经网络的二层多任务回归神经网络,用于通过交叉STICH网络的并行数字预测任务,允许各种并行数字预测任务之间的信息/模型参数共享。

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