cambridgeltl/eva
[AAAI'21] Code release for "Visual Pivoting for (Unsupervised) Entity Alignment".
EVA helps researchers and knowledge graph developers to identify and link identical real-world entities across different knowledge graphs, even when entity names or descriptions vary. It takes in existing knowledge graphs, optionally with associated images for entities, and outputs a mapping of equivalent entities between them. This is particularly useful for those working with large, diverse knowledge bases and needing to consolidate or cross-reference information.
No commits in the last 6 months.
Use this if you need to precisely match and link entities (like people, places, or organizations) from different knowledge graphs, especially when visual information associated with entities can aid in the matching process.
Not ideal if your knowledge graphs do not contain image data for entities or if you only need to align knowledge graphs based on textual information.
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34
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7
Language
Python
License
MIT
Category
Last pushed
Jan 23, 2022
Commits (30d)
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