منابع مشابه
Uncertain Temporal Knowledge Graphs
Temporal data can be found in various sources from patient histories, purchase histories, employee histories, to web logs. Recent advances in open information extraction have paved the way for automatic construction of knowledge graphs (kgs) from such sources. Often the extraction tools used to construct kgs produce facts and rules along with their confidence scores, leading to the notion of un...
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Embedding knowledge graphs into continuous vector spaces has recently attracted increasing interest. Most existing methods perform the embedding task using only fact triples. Logical rules, although containing rich background information, have not been well studied in this task. This paper proposes a novel method of jointly embedding knowledge graphs and logical rules. The key idea is to repres...
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The aim of knowledge graphs is to gather knowledge about the world and provide a structured representation of this knowledge. Current knowledge graphs are far from complete. To address the incompleteness of the knowledge graphs, link prediction approaches have been developed which make probabilistic predictions about new links in a knowledge graph given the existing links. Tensor factorization ...
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Representation learning of knowledge graphs encodes entities and relation types into a continuous low-dimensional vector space, learns embeddings of entities and relation types. Most existing methods only concentrate on knowledge triples, ignoring logic rules which contain rich background knowledge. Although there has been some work aiming at leveraging both knowledge triples and logic rules, t...
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A drawing of a graph G in the plane is weakly simple if it can be turned into an embedding by an arbitrarily small perturbation. We show that testing, whether a straight-line drawing of a planar graph G in the plane is weakly simple, can be carried out in polynomial time, if a desired embedding of G belongs to a fixed isotopy class. In other words, we show that c-planarity with pipes is tractab...
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ژورنال
عنوان ژورنال: Proceedings of the AAAI Conference on Artificial Intelligence
سال: 2019
ISSN: 2374-3468,2159-5399
DOI: 10.1609/aaai.v33i01.33013363