Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Fabian Suchanek"'
Autor:
Jérôme Dockès, Russell A Poldrack, Romain Primet, Hande Gözükan, Tal Yarkoni, Fabian Suchanek, Bertrand Thirion, Gaël Varoquaux
Publikováno v:
eLife, Vol 9 (2020)
Reaching a global view of brain organization requires assembling evidence on widely different mental processes and mechanisms. The variety of human neuroscience concepts and terminology poses a fundamental challenge to relating brain imaging results
Externí odkaz:
https://doaj.org/article/8bfa4bfc15854b36809841a2a40bca7b
Autor:
Paul Groth, Maria-Esther Vidal, Fabian Suchanek, Pedro Szekley, Pavan Kapanipathi, Catia Pesquita, Hala Skaf-Molli, Minna Tamper
Publikováno v:
The Semantic Web ISBN: 9783031069802
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c58df4fd623a08809bf2d561cb814a01
https://doi.org/10.1007/978-3-031-06981-9_29
https://doi.org/10.1007/978-3-031-06981-9_29
Autor:
Riccardo Tommasini, Senjuti Basu Roy, Xuan Wang, Hongwei Wang, Heng Ji, Jiawei Han, Preslav Nakov, Giovanni Da San Martino, Firoj Alam, Markus Schedl, Elisabeth Lex, Akash Bharadwaj, Graham Cormode, Milan Dojchinovski, Jan Forberg, Johannes Frey, Pieter Bonte, Marco Balduini, Matteo Belcao, Emanuele Della Valle, Junliang Yu, Hongzhi Yin, Tong Chen, Haochen Liu, Yiqi Wang, Wenqi Fan, Xiaorui Liu, Jamell Dacon, Lingjuan Lye, Jiliang Tang, Aristides Gionis, Stefan Neumann, Bruno Ordozgoiti, Simon Razniewski, Hiba Arnaout, Shrestha Ghosh, Fabian Suchanek, Lingfei Wu, Yu Chen, Yunyao Li, Bang Liu, Filip Ilievski, Daniel Garijo, Hans Chalupsky, Pedro Szekely, Ilias Kanellos, Dimitris Sacharidis, Thanasis Vergoulis, Nurendra Choudhary, Nikhil Rao, Karthik Subbian, Srinivasan Sengamedu, Chandan K. Reddy, Friedhelm Victor, Bernhard Haslhofer, George Katsogiannis- Meimarakis, Georgia Koutrika, Shengmin Jin, Danai Koutra, Reza Zafarani, Yulia Tsvetkov, Vidhisha Balachandran, Sachin Kumar, Xiangyu Zhao, Bo Chen, Huifeng Guo, Yejing Wang, Ruiming Tang, Yang Zhang, Wenjie Wang, Peng Wu, Fuli Feng, Xiangnan He
This paper summarizes the content of the 20 tutorials that have been given at The Web Conference 2022: 85% of these tutorials are lecture style, and 15% of these are hands on. Published version
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::646b27f2a0da768c4c9127736ec92e15
https://hdl.handle.net/10919/112211
https://hdl.handle.net/10919/112211
Publikováno v:
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5e93fe83258d4830ed34f55e077eeed9
https://doi.org/10.18653/v1/2022.acl-long.245
https://doi.org/10.18653/v1/2022.acl-long.245
Autor:
Paul Groth, Maria-Esther Vidal, Fabian Suchanek, Pedro Szekley, Pavan Kapanipathi, Catia Pesquita, Hala Skaf-Molli, Minna Tamper
Chapters “No. 10 and No. 21” are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Equipping machines with comprehensive knowledge of the world's entities and their relationships has been a longstanding goal of AI. Over the last decade, large-scale knowledge bases, also known as knowledge graphs, have been automatically constructed
Publikováno v:
WWW
World Wide Web Conference
World Wide Web Conference, May 2019, San Francisco, United States. ⟨10.1145/3308558.3313584⟩
World Wide Web Conference
World Wide Web Conference, May 2019, San Francisco, United States. ⟨10.1145/3308558.3313584⟩
International audience; The curation of a knowledge base is a crucial but costly task. In this work, we propose to take advantage of the edit history of the knowledge base in order to learn how to correct constraint violations. Our method is based on
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dd8df4bfe6e571056e68ea01cb3445ab
https://doi.org/10.1145/3308558.3313584
https://doi.org/10.1145/3308558.3313584
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering (TKDE)
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2020, ⟨10.1109/TKDE.2020.3018741⟩
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2020, ⟨10.1109/TKDE.2020.3018741⟩
International audience; Entity alignment (EA) finds equivalent entities that are located in different knowledge graphs (KGs), which is an essential step to enhance the quality of KGs, and hence of significance to downstream applications (e.g., questi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::94f9a42e19a32b06cb2b571b7af235b4
https://doi.org/10.1109/tkde.2020.3018741
https://doi.org/10.1109/tkde.2020.3018741
Publikováno v:
15th International Semantic Web Conference
ISWC: International Semantic Web Conference
ISWC: International Semantic Web Conference, Oct 2016, Kobe, Japan
HAL
ISWC: International Semantic Web Conference
ISWC: International Semantic Web Conference, Oct 2016, Kobe, Japan
HAL
International audience; In this demonstration paper, we present a system for computer-assisted brainstorming, i.e., for generating hypotheses to aid human creativity. More precisely, given an input concept (such as “car”), our system proposes var
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::c65ccec27fd832101845b4bbf4256c94
https://hal-lirmm.ccsd.cnrs.fr/lirmm-01400409/file/SucMenBieCha-demo-ISWC16.pdf
https://hal-lirmm.ccsd.cnrs.fr/lirmm-01400409/file/SucMenBieCha-demo-ISWC16.pdf