CoChat
Sign Up
Cited by 406

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

HyTE: Hyperplane-based Temporally aware Knowledge Graph Embedding

Dasgupta, Shib Sankar, Ray, Swayambhu Nath, Talukdar, Partha·2018·Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
DOI 10.18653/v1/d18-1225
Open this paper in CoChat — free account

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.18653/v1/d18-1225

Cites

3 of 3 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • [Dasgupta et al., 2018] regards timestamps as hyperplanes that segregate the temporal space into discrete time zones.

    “Specifically, [Dasgupta et al., 2018] regards timestamps as hyperplanes, which segregate the temporal space into discrete time zones.”

    From Temporal Knowledge Graph Completion: A Survey (2023) · cites this paper as Dasgupta et al., 2018

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Flagged first, then by citations

Research works printed but not linked: 29

  1. Kurt Bollacker, Colin Evans, Praveen Paritosh, Tim Sturge, and Jamie Taylor. 2008. Freebase: A col- laboratively created graph database for structuring human knowledge. In Proceedings of the 2008 ACM SIGMOD International Conference on Man- agement of Data, SIGMOD '08, pages 1247-1250, New York, NY, USA. ACM. · DOI · Paper page
  2. Antoine Bordes, Nicolas Usunier, Alberto Garcia- Duran, Jason Weston, and Oksana Yakhnenko. 2013. Translating embeddings for modeling multi- relational data. In C. J. C. Burges, L. Bottou, M. Welling, Z. Ghahramani, and K. Q. Weinberger, editors, Advances in Neural Information Processing Systems 26, pages 2787-2795.
  3. Tim Dettmers, Pasquale Minervini, Pontus Stenetorp, and Sebastian Riedel. 2018. Convolutional 2d knowledge graph embeddings. In Proceedings of the Thirty-Second AAAI Conference on Artificial In- telligence, New Orleans, Louisiana, USA, February 2-7, 2018.
  4. Li Dong, Furu Wei, Ming Zhou, and Ke Xu. 2015. Question answering over freebase with multi- column convolutional neural networks. In Proceed- ings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th Interna- tional Joint Conference on Natural Language Pro- cessing of the Asian Federation of Natural Language Processing, ACL 2015, July 26-31, 2015, Beijing, China, Volume 1: Long Papers, pages 260-269.
  5. Fredo Erxleben, Michael Günther, Markus Krötzsch, Julian Mendez, and Denny Vrandeȃić. 2014. Intro- ducing wikidata to the linked data web. In Proceed- ings of the 13th International Semantic Web Confer- ence -Part I, ISWC '14, pages 50-65, New York, NY, USA. Springer-Verlag New York, Inc. · DOI
  6. Shu Guo, Quan Wang, Lihong Wang, Bin Wang, and Li Guo. 2018. Knowledge graph embedding with it- erative guidance from soft rules. In Proceedings of the Thirty-Second AAAI Conference on Artificial In- telligence, New Orleans, Louisiana, USA, February 2-7, 2018.
  7. Guoliang Ji, Shizhu He, Liheng Xu, Kang Liu, and Jun Zhao. 2015. Knowledge graph embedding via dynamic mapping matrix. In Proceedings of the 53rd Annual Meeting of the Association for Compu- tational Linguistics and the 7th International Joint Conference on Natural Language Processing (Vol- ume 1: Long Papers), volume 1, pages 687-696.
  8. Tingsong Jiang, Tianyu Liu, Tao Ge, Lei Sha, Sujian Li, Baobao Chang, and Zhifang Sui. 2016. Encod- ing temporal information for time-aware link pre- diction. In Proceedings of the 2016 Conference on Empirical Methods in Natural Language Process- ing, pages 2350-2354. Association for Computa- tional Linguistics. · DOI
  9. Alexander Kotov and ChengXiang Zhai. 2012. Tap- ping into knowledge base for concept feedback: Leveraging conceptnet to improve search results for difficult queries. In Proceedings of the Fifth ACM International Conference on Web Search and Data Mining, WSDM '12, pages 403-412, New York, NY, USA. ACM. · DOI
  10. Julien Leblay and Melisachew Wudage Chekol. 2018. Deriving validity time in knowledge graph. In Companion Proceedings of the The Web Conference 2018, WWW '18, pages 1771-1776, Republic and Canton of Geneva, Switzerland. International World Wide Web Conferences Steering Committee. · DOI · Paper page
  11. Yankai Lin, Zhiyuan Liu, Maosong Sun, Yang Liu, and Xuan Zhu. 2015. Learning entity and relation em- beddings for knowledge graph completion. In Pro- ceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, AAAI'15, pages 2181-2187. AAAI Press.
  12. Bill McDowell, Nathanael Chambers, Alexander Oror- bia II, and David Reitter. 2017. Event ordering with a generalized model for sieve prediction ranking. In Proceedings of the Eighth International Joint Con- ference on Natural Language Processing (Volume 1: Long Papers), pages 843-853, Taipei, Taiwan. Asian Federation of Natural Language Processing.
  13. Paramita Mirza and Sara Tonelli. 2016. Catena: Causal and temporal relation extraction from natural lan- guage texts. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, pages 64-75. The COLING 2016 Organizing Committee.
  14. T. Mitchell, W. Cohen, E. Hruschka, P. Talukdar, B. Yang, J. Betteridge, A. Carlson, B. Dalvi, M. Gardner, B. Kisiel, J. Krishnamurthy, N. Lao, K. Mazaitis, T. Mohamed, N. Nakashole, E. Pla- tanios, A. Ritter, M. Samadi, B. Settles, R. Wang, D. Wijaya, A. Gupta, X. Chen, A. Saparov, M. Greaves, and J. Welling. 2018. Never-ending learning. Communications of the ACM, 61(5):103- 115.
  15. Maximilian Nickel, Kevin Murphy, Volker Tresp, and Evgeniy Gabrilovich. 2016a. A review of relational machine learning for knowledge graphs. Proceed- ings of the IEEE, 104(1):11-33. · DOI
  16. Maximilian Nickel, Lorenzo Rosasco, and Tomaso Poggio. 2016b. Holographic embeddings of knowl- edge graphs. In Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, AAAI'16, pages 1955-1961. AAAI Press.
  17. Maximilian Nickel, Volker Tresp, and Hans-Peter Kriegel. 2011. A three-way model for collective learning on multi-relational data. In Proceedings of the 28th International Conference on International Conference on Machine Learning, ICML'11, pages 809-816, USA.
  18. Baoxu Shi and Tim Weninger. 2018. Open-world knowledge graph completion. In Proceedings of the Thirty-Second AAAI Conference on Artificial Intelli- gence, New Orleans, Louisiana, USA, February 2-7, 2018.
  19. Richard Socher, Danqi Chen, Christopher D Manning, and Andrew Ng. 2013. Reasoning with neural ten- sor networks for knowledge base completion. In C. J. C. Burges, L. Bottou, M. Welling, Z. Ghahra- mani, and K. Q. Weinberger, editors, Advances in Neural Information Processing Systems 26, pages 926-934.
  20. Fabian M. Suchanek, Gjergji Kasneci, and Gerhard Weikum. 2007. Yago: A Core of Semantic Knowl- edge. In 16th International Conference on the World Wide Web, pages 697-706.
  21. Partha Pratim Talukdar, Derry Wijaya, and Tom Mitchell. 2012a. Acquiring temporal constraints be- tween relations. In Proceedings of the 21st ACM international conference on Information and knowl- edge management, pages 992-1001. ACM.
  22. Partha Pratim Talukdar, Derry Wijaya, and Tom Mitchell. 2012b. Coupled temporal scoping of rela- tional facts. In Proceedings of the Fifth ACM Inter- national Conference on Web Search and Data Min- ing, WSDM '12, pages 73-82, New York, NY, USA. ACM. · DOI · Paper page
  23. Rakshit Trivedi, Hanjun Dai, Yichen Wang, and Le Song. 2017. Know-evolve: Deep temporal rea- soning for dynamic knowledge graphs. In Proceed- ings of the 34th International Conference on Ma- chine Learning.
  24. Naushad UzZaman, Hector Llorens, Leon Derczyn- ski, James Allen, Marc Verhagen, and James Puste- jovsky. 2013. Semeval-2013 task 1: Tempeval-3: Evaluating time expressions, events, and temporal relations. In Second Joint Conference on Lexical and Computational Semantics (* SEM), Volume 2: Proceedings of the Seventh International Workshop on Semantic Evaluation (SemEval 2013), volume 2, pages 1-9.
  25. Marc Verhagen, Roser Sauri, Tommaso Caselli, and James Pustejovsky. 2010. Semeval-2010 task 13: Tempeval-2. In Proceedings of the 5th international workshop on semantic evaluation, pages 57-62. As- sociation for Computational Linguistics.
  26. Yafang Wang, Mingjie Zhu, Lizhen Qu, Marc Spaniol, and Gerhard Weikum. 2010. Timely yago: Harvest- ing, querying, and visualizing temporal knowledge from wikipedia. In Proceedings of the 13th Inter- national Conference on Extending Database Tech- nology, EDBT '10, pages 697-700, New York, NY, USA. ACM. · DOI · Paper page
  27. Chenyan Xiong and Jamie Callan. 2015. Query ex- pansion with freebase. In Proceedings of the 2015 International Conference on The Theory of Infor- mation Retrieval, ICTIR '15, pages 111-120, New York, NY, USA. ACM. · DOI
  28. Bishan Yang, Wen-tau Yih, Xiaodong He, Jianfeng Gao, and Li Deng. 2014. Embedding entities and relations for learning and inference in knowledge bases. arXiv preprint arXiv:1412.6575. · arXiv
  29. Xuchen Yao and Benjamin Van Durme. 2014. Infor- mation extraction over structured data: Question an- swering with freebase. In Proceedings of the 52nd Annual Meeting of the Association for Computa- tional Linguistics, ACL 2014, June 22-27, 2014, Baltimore, MD, USA, Volume 1: Long Papers, pages 956-966.

Cited by

Sorted by citations

Metadata

Authors
Dasgupta, S. S., Ray, S. N., & Talukdar, P.
Venue
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
Publisher
Association for Computational Linguistics
Published
2018
Pages
2001-2011
DOI
10.18653/v1/d18-1225
Cited by
406
References
3

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review