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task ID: tripleclassification

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Context-Dependent Knowledge Graph Embedding

Authors: nan

Publication: TIPSTER (2015)

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We consider the problem of embedding knowledge graphs (KGs) into continuous vector spaces. Existing methods can on- ly deal with explicit relationships within each triple, i.e., local connectivity pattern- s, …...

34440

Encoding Temporal Information for Time-Aware Link Prediction

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Publication: TIPSTER (2016)

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Most existing knowledge base (KB) embed- ding methods solely learn from time-unknown fact triples but neglect the temporal informa- tion in the knowledge base. In this paper, we propose a …...

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Jointly Embedding Knowledge Graphs and Logical Rules

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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. Logi- cal rules, although containing rich background …...

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Neighborhood Mixture Model for Knowledge Base Completion

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Publication: TIPSTER (2016)

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Knowledge bases are useful resources for many natural language processing tasks, however, they are far from complete. In this paper, we define a novel entity rep- resentation as a mixture …...

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A Multimodal Translation-Based Approach for Knowledge Graph Representation Learning

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AbstractCurrent methods for knowledge graph (KG) representation learning focus solely on the structure of the KG and do not exploit any kind of external information, such as visual and linguistic …...

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Accurate Text-Enhanced Knowledge Graph Representation Learning

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AbstractPrevious representation learning techniques for knowledge graph representation usually represent the same entity or relation in different triples with the same representation, without considering the ambiguity of relations and entities. …...

22310