https://github.com/aksw/kg2vec
🏎 KG2Vec: Expeditious Generation of Knowledge Graph Embeddings
Science Score: 10.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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○codemeta.json file
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○.zenodo.json file
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○DOI references
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✓Academic publication links
Links to: arxiv.org -
○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (5.5%) to scientific vocabulary
Repository
🏎 KG2Vec: Expeditious Generation of Knowledge Graph Embeddings
Basic Info
- Host: GitHub
- Owner: AKSW
- License: mit
- Language: Python
- Default Branch: master
- Homepage: http://tsoru.aksw.org/kg2vec/
- Size: 241 KB
Statistics
- Stars: 28
- Watchers: 25
- Forks: 12
- Open Issues: 1
- Releases: 0
Metadata Files
README.md
KG2Vec
🏎 KG2Vec: Expeditious Generation of Knowledge Graph Embeddings
Usage
- Download data from http://tsoru.aksw.org/kg2vec/
bash
sh kg2vec_<scoring>.sh <dataset_id> <training_data> <dimensions> <test_data> <verbalization_type> <neg_sampling> <training_epochs>
LSTM-based scoring function
bash
sh kg2vec_lstm.sh aksw-bib aksw-bib.train+valid.nt 10 aksw-bib.test.nt output random 100
Analogy-based scoring function
bash
sh kg2vec_analogy.sh aksw-bib aksw-bib.train+valid.nt 10 aksw-bib.test.nt output
Use cases
- An add-on for the Genesis Linked Data browser uses a low-dimensional KG2Vec model trained on DBpedia for retrieving similar resources.
Cite
- Presented at the 5th European Conference on Data Analysis (ECDA 2018) as "A Simple and Fast Approach to Knowledge Graph Embedding".
- Working paper: https://arxiv.org/abs/1803.07828
bib
@proceedings{soru-kg2vec-2018,
author = "Tommaso Soru and Stefano Ruberto and Diego Moussallem and Edgard Marx and Diego Esteves and Axel-Cyrille {Ngonga Ngomo}",
title = "Expeditious Generation of Knowledge Graph Embeddings",
year = "2018",
}
Owner
- Name: AKSW Research Group @ University of Leipzig
- Login: AKSW
- Kind: organization
- Location: Leipzig
- Website: http://aksw.org
- Repositories: 358
- Profile: https://github.com/AKSW
GitHub Events
Total
- Watch event: 1
Last Year
- Watch event: 1
Dependencies
- gensim ==2.1.0
- keras ==2.2.4
- rdflib ==4.2.2
- tensorflow ==1.15.2