Generating Contextual Weighted Commonsense Knowledge Graphs

Author:

Rezaei NavidORCID,Reformat Marek Z.ORCID,Yager Ronald R.ORCID

Publisher

Springer International Publishing

Reference25 articles.

1. Benferhat, S., Dubois, D., Garcia, L., Prade, H.: Possibilistic logic bases and possibilistic graphs. In: Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence, pp. 57–64. UAI 1999. Morgan Kaufmann Publishers Inc., San Francisco (1999)

2. Chamorro-Martínez, J., et al.: Referring expression generation from images via deep learning object extraction and fuzzy graphs. In: 2021 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE, pp. 1–6 (2021)

3. Chen, X., Shrivastava, A., Gupta, A.: NEIL: extracting visual knowledge from web data. In: 2013 IEEE International Conference on Computer Vision, pp. 1409–1416 (2013)

4. Divvala, S.K., Farhadi, A., Guestrin, C.: Learning everything about anything: webly-supervised visual concept learning. In: 2014 IEEE Conference on Computer Vision and Pattern Recognition, pp. 3270–3277 (2014)

5. Dubois, D., Prade, H.: Possibility Theory: An Approach to Computerized Processing of Uncertainty. Springer, US (1988)

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