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SYSTEM AND METHOD TO DISCOVER MEANINGFUL PATHS FROM LINKED OPEN DATA

机译:从链接的开放数据中发现有意义的路径的系统和方法

摘要

A method, a system and a computer program product for searching a knowledge base and finding top-k meaningful paths for different concept pairs input by a user in linked open data utilizing the degree of association between concepts as the weight of the two concepts in a knowledge graph and to find the top-k shortest path as meaningful paths. A large corpus is used to train the association of different concept pairs. A deep learning based framework is used to learn a concept vector to represent the concept and the cosine similarity of the concept vector and an input concept vector indicating the degree of association of the vectors as the weight of these two concepts in the knowledge graph. The top-k meaningful paths are determined based on the weights and the shortest paths are provided for use by users as the meaningful paths.
机译:一种方法,系统和计算机程序产品,该方法,系统和计算机程序产品利用概念之间的关联度作为两个概念中的权重,在链接的开放数据中查找用户输入的不同概念对的前k个有意义的路径。知识图并找到前k个最短路径作为有意义的路径。大型语料库用于训练不同概念对的关联。基于深度学习的框架用于学习概念向量,以表示概念和概念向量的余弦相似度,以及输入概念向量,指示输入向量的关联程度,作为知识图中这两个概念的权重。根据权重确定前k个有意义的路径,并提供最短的路径供用户用作有意义的路径。

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