DAGOBAH: Enhanced Scoring Algorithms for Scalable Annotations of Tabular Data

Viet-Phi Huynh, Jixiong Liu, Yoan Chabot, Thomas Labbé, Pierre Monnin, Raphaël Troncy. DAGOBAH: Enhanced Scoring Algorithms for Scalable Annotations of Tabular Data. In Ernesto Jiménez-Ruiz, Oktie Hassanzadeh, Vasilis Efthymiou, Jiaoyan Chen, Kavitha Srinivas, Vincenzo Cutrona, editors, Proceedings of the Semantic Web Challenge on Tabular Data to Knowledge Graph Matching (SemTab 2020) co-located with the 19th International Semantic Web Conference (ISWC 2020), Virtual conference (originally planned to be in Athens, Greece), November 5, 2020. Volume 2775 of CEUR Workshop Proceedings, pages 27-39, CEUR-WS.org, 2020. [doi]

@inproceedings{HuynhLCLMT20,
  title = {DAGOBAH: Enhanced Scoring Algorithms for Scalable Annotations of Tabular Data},
  author = {Viet-Phi Huynh and Jixiong Liu and Yoan Chabot and Thomas Labbé and Pierre Monnin and Raphaël Troncy},
  year = {2020},
  url = {http://ceur-ws.org/Vol-2775/paper3.pdf},
  researchr = {https://researchr.org/publication/HuynhLCLMT20},
  cites = {0},
  citedby = {0},
  pages = {27-39},
  booktitle = {Proceedings of the Semantic Web Challenge on Tabular Data to Knowledge Graph Matching (SemTab 2020) co-located with the 19th International Semantic Web Conference (ISWC 2020), Virtual conference (originally planned to be in Athens, Greece), November 5, 2020},
  editor = {Ernesto Jiménez-Ruiz and Oktie Hassanzadeh and Vasilis Efthymiou and Jiaoyan Chen and Kavitha Srinivas and Vincenzo Cutrona},
  volume = {2775},
  series = {CEUR Workshop Proceedings},
  publisher = {CEUR-WS.org},
}