Semanlink - Bootstrapping Entity Alignment with Knowledge Graph Embedding

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sl:bookmarkOf : https://www.ijcai.org/Proceedings/2018/611
sl:creationDate : 2020-05-11
sl:creationTime : 2020-05-11T21:59:04Z

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2020-09-06 A propos

[1902.10197] RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space

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Knowledge Graph Embedding: A Survey of Approaches and Applications - IEEE (2017)

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- "facts only" based embeddings
    - Translational Distance Models, distance-based scoring functions
       - TransE and co: entities and relations as points in vector space
           - TransH: relation-specific hyperplanes.
       - Gaussian Embeddings: entities and relations as random variables
    - Semantic matching models, similarity-based scoring functions
        - RESCAL (entities as a vector, relation as a matrix) and familiy
            - DistMult (relation as diagonal matrix)
            - Holographic Embeddings (HolE)
            - etc.
        - Matching with Neural Networks
            - SME, etc
- incorporating other info: entity types, relation paths,
textual descriptions, as well as logical rules
    - entity types
        - semantically smooth embedding
(SSE):  entities of the same type to stay close
to each other in the embedding space
        - type-embodied knowledge representation
learning (TKRL), which can handle hierarchical
entity categories and multiple category labels
- Applications in downstream tasks

2019-05-27 A propos