* Satoshi Hara and Kohei Hayashi. Making Tree Ensembles Interpretable: A Bayesian Model Selection Approach. AISTATS'18 (to appear).
arXiv ver.: https://arxiv.org/abs/1606.09066#
* GitHub
https://github.com/sato9hara/defragTrees
LODチャレンジ2022授賞式シンポジウムでの紹介スライドです。
受賞作品:https://github.com/KnowledgeGraphJapan/KGRC-RDF/blob/kgrc4si/extended_readme.md
受賞情報:https://2022.lodc.jp/awardPressRelease2022.html
引用:
江上周作,鵜飼孝典,窪田文也,大野美喜子,北村光司,福田賢一郎: 家庭内の事故予防に向けた合成ナレッジグラフの構築と推論,第56回人工知能学会セマンティックウェブとオントロジー研究会, SIG-SWO-056-14 (2022) DOI: https://doi.org/10.11517/jsaisigtwo.2022.SWO-056_14
Egami, S., Nishimura, S., Fukuda, K.: A Framework for Constructing and Augmenting Knowledge Graphs using Virtual Space: Towards Analysis of Daily Activities. Proceedings of the 33rd IEEE International Conference on Tools with Artificial Intelligence. pp.1226-1230 (2021) DOI: https://doi.org/10.1109/ICTAI52525.2021.00194
Egami, S., Nishimura, S., Fukuda, K.: VirtualHome2KG: Constructing and Augmenting Knowledge Graphs of Daily Activities Using Virtual Space. Proceedings of the ISWC 2021 Posters, Demos and Industry Tracks: From Novel Ideas to Industrial Practice, co-located with 20th International Semantic Web Conference. CEUR, Vol.2980 (2021) https://ceur-ws.org/Vol-2980/paper381.pdf
* Satoshi Hara and Kohei Hayashi. Making Tree Ensembles Interpretable: A Bayesian Model Selection Approach. AISTATS'18 (to appear).
arXiv ver.: https://arxiv.org/abs/1606.09066#
* GitHub
https://github.com/sato9hara/defragTrees
LODチャレンジ2022授賞式シンポジウムでの紹介スライドです。
受賞作品:https://github.com/KnowledgeGraphJapan/KGRC-RDF/blob/kgrc4si/extended_readme.md
受賞情報:https://2022.lodc.jp/awardPressRelease2022.html
引用:
江上周作,鵜飼孝典,窪田文也,大野美喜子,北村光司,福田賢一郎: 家庭内の事故予防に向けた合成ナレッジグラフの構築と推論,第56回人工知能学会セマンティックウェブとオントロジー研究会, SIG-SWO-056-14 (2022) DOI: https://doi.org/10.11517/jsaisigtwo.2022.SWO-056_14
Egami, S., Nishimura, S., Fukuda, K.: A Framework for Constructing and Augmenting Knowledge Graphs using Virtual Space: Towards Analysis of Daily Activities. Proceedings of the 33rd IEEE International Conference on Tools with Artificial Intelligence. pp.1226-1230 (2021) DOI: https://doi.org/10.1109/ICTAI52525.2021.00194
Egami, S., Nishimura, S., Fukuda, K.: VirtualHome2KG: Constructing and Augmenting Knowledge Graphs of Daily Activities Using Virtual Space. Proceedings of the ISWC 2021 Posters, Demos and Industry Tracks: From Novel Ideas to Industrial Practice, co-located with 20th International Semantic Web Conference. CEUR, Vol.2980 (2021) https://ceur-ws.org/Vol-2980/paper381.pdf
Knowledge Graph Reasoning Techniques through Studies on Mystery Stories - Rep...KnowledgeGraph
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1) The document summarizes the Knowledge Graph Reasoning Challenge (KGRC) held from 2018 to 2020.
2) The challenge task involved developing AI systems that can reason about and solve mysteries presented as open knowledge graphs based on Sherlock Holmes stories, providing reasonable explanations.
3) Over the three years of the challenge, 24 systems were submitted using various approaches like knowledge processing, machine learning, or combinations, and making use of different external knowledge resources. The challenge aims to promote techniques for explainable AI using knowledge graph reasoning.
Report on the First Knowledge Graph Reasoning Challenge 2018 -Toward the eXp...KnowledgeGraph
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JIST2019: The 9th Joint International Semantic Technology Conference
The premium Asian forum on Semantic Web, Knowledge Graph, Linked Data and AI on the Web. Nov. 25-27, 2019, Hangzhou, China.
http://jist2019.openkg.cn/