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Mulang' I Onando
Mulang' I Onando
Research Scientist @IBM-Research Africa, and Mentor @Zerotha Research
Verified email at ibm.com - Homepage
Title
Cited by
Cited by
Year
Old is Gold: Linguistic Driven Approach for Entity and Relation Linking of Short Text
A Sakor, IO Mulang', K Singh, S Shekarpour, ME Vidal, J Lehmann, ...
NAACL-HLT, 2019
662019
Matching Natural Language Relations to Knowledge Graph Properties for Question Answering
IO Mulang', K Singh, F Orlandi
In proceedings of Semantics 2017, Amsterdam, Netherlands, 2017
362017
Evaluating the Impact of Knowledge Graph Context On Entity Disambiguation Models
IO Mulang', K Singh, C Prabhu, A Nadgeri, J Hoffart, J Lehmann
CIKM'20, 2020
302020
Capturing Knowledge in Semantically-typed Relational Patterns to Enhance Relation Linking
K Singh, IO Mulang', M Yaser, A Sakor, ME Vidal, C Lange, S Auer
Knowledge Capture (K-Cap 2017), 2017
242017
RECON: Relation Extraction using Knowledge Graph Context in a Graph Neural Network
A Bastos, A Nadgeri, K Singh, IO Mulang, S Shekarpour, J Hoffart
The Web Conference (WWW'21), 2021
172021
Encoding Knowledge Graph Entity Aliases in Attentive Neural Network for Wikidata Entity Linking
IO Mulang', K Singh, A Vyas, S Shekarpour, ME Vidal, S Auer, J Lehmann
Web Information Systems Engineering (WISE 2020), 2020
13*2020
CHOLAN: A Modular Approach for Neural Entity Linking on Wikipedia and Wikidata
MPK Ravi, K Singh, IO Mulang', S Shekarpour, J Hoffart, J Lehmann
EACL-2021 (Full Paper), 2021
82021
Team SVMrank: Leveraging Feature-rich Support Vector Machines for Ranking Explanations to Elementary Science Questions
J D’Souza, IO Mulang', S Auer
EMNLP | Proceedings of the Thirteenth Workshop on Graph-Based Methods for …, 2019
52019
Kgpool: Dynamic knowledge graph context selection for relation extraction
A Nadgeri, A Bastos, K Singh, IO Mulang, J Hoffart, S Shekarpour, ...
arXiv preprint arXiv:2106.00459, 2021
42021
Automated supervised feature selection for differentiated patterns of care
C Wanjiru, W Ogallo, GA Tadesse, C Wachira, IO Mulang, ...
arXiv preprint arXiv:2111.03495, 2021
22021
Post-discovery Analysis of Anomalous Subsets
IO Mulang, W Ogallo, GA Tadesse, A Walcott-Bryant
arXiv preprint arXiv:2111.14622, 2021
12021
Hopfe: Knowledge graph representation learning using inverse hopf fibrations
A Bastos, K Singh, A Nadgeri, S Shekarpour, IO Mulang, J Hoffart
Proceedings of the 30th ACM International Conference on Information …, 2021
12021
Fine-tuning BERT with Focus Words for Explanation Regeneration
IO Mulang', J D’Souza, S Auer
Proceedings of the Ninth Joint Conference on Lexical and Computational …, 2020
12020
Social Media Temporal Absence Recommendation: a Collaborative Filtering Perspective
IO Mulang'
12015
Ranking Facts for Explaining Answers to Elementary Science Questions
J D'Souza, IO Mulang', S Auer
https://www.doi.org/10.1017/S1351324921000358, 2022
2022
Sparsity-based Feature Selection for Anomalous Subgroup Discovery
GA Tadesse, W Ogallo, C Wanjiru, C Wachira, IO Mulang, V Anand, ...
arXiv preprint arXiv:2201.02008, 2022
2022
Knowledge Context for Entity and Relation Linking (Ph.D. Thesis)
IM Onando
Universitäts-und Landesbibliothek Bonn, 2021
2021
Correction to: Encoding Knowledge Graph Entity Aliases in Attentive Neural Network for Wikidata Entity Linking
IO Mulang', K Singh, A Vyas, S Shekarpour, ME Vidal, J Lehmann, S Auer
International Conference on Web Information Systems Engineering, C1-C1, 2020
2020
Temporal Absence in Recommendations: a survey of Temporal Patterns in Netflix Prize Data
IO Mulang', W Mwangi
International Journal of Computer Science Issues (IJCSI) 11 (4), 92, 2014
2014
Team Name: Leveraging Feature-rich Support Vector Machines for Ranking Explanations to Elementary Science Questions
J D’Souza, IO Mulang', S Auer
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Articles 1–20