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Tensor Decomposition for Link Prediction in Temporal Knowledge Graphs

Published: 02 December 2021 Publication History

Abstract

We study temporal knowledge graph completion by using tensor decomposition. In particular, we use Candecomp/Parafac decomposition to factorize a given four dimensional sparse representation of a temporal knowledge graph into rank-one tensors that correspond to entities (subject and object), relations and timestamps. Using the factorized tensors, we can perform link and timestamp prediction. We compared our approach against the state of the art and found out that we are highly competitive. We report our preliminary experimental results on 5 different datasets.

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Cited By

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  • (2024)Meta-learning framework with updating information flow for enhancing inductive predictionKnowledge-Based Systems10.1016/j.knosys.2024.111720294:COnline publication date: 21-Jun-2024
  • (2023)TemporalFC: A Temporal Fact Checking Approach over Knowledge GraphsThe Semantic Web – ISWC 202310.1007/978-3-031-47240-4_25(465-483)Online publication date: 6-Nov-2023

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cover image ACM Conferences
K-CAP '21: Proceedings of the 11th Knowledge Capture Conference
December 2021
300 pages
ISBN:9781450384575
DOI:10.1145/3460210
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 02 December 2021

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Author Tags

  1. graph embedding
  2. link prediction
  3. temporal knowledge graph

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K-CAP '21
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K-CAP '21: Knowledge Capture Conference
December 2 - 3, 2021
Virtual Event, USA

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Cited By

View all
  • (2024)Meta-learning framework with updating information flow for enhancing inductive predictionKnowledge-Based Systems10.1016/j.knosys.2024.111720294:COnline publication date: 21-Jun-2024
  • (2023)TemporalFC: A Temporal Fact Checking Approach over Knowledge GraphsThe Semantic Web – ISWC 202310.1007/978-3-031-47240-4_25(465-483)Online publication date: 6-Nov-2023

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