Dr. Isaiah Onando Mulang’ left SDA. The profile below reflects the status at the point of his departure and is no longer updated.
Computer Science Institute
University of Bonn
Profiles: LinkedIn, Google Scholar
Endenicher Allee 19a, 53115 Bonn
University of Bonn, Computer Science
Isaiah Onando Mulang’ is a PhD Student at the University of Bonn. Isaiah’ research interests are in the area of Matching NL relations to KG properties (Rules, embeddings & future PGM).
- Machine Learning & Deep Learning for NLP, KG, Social Media, and BI
- Distributional Semantics and Grammar
KGPool: Dynamic Knowledge Graph Context Selection for Relation Extraction Inproceedings
In: Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, Online Event, August 1-6, 2021, pp. 535–548, Association for Computational Linguistics, 2021.
HopfE: Knowledge Graph Representation Learning using Inverse Hopf Fibrations Inproceedings
In: CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1 - 5, 2021, pp. 89–99, ACM, 2021.
CHOLAN: A Modular Approach for Neural Entity Linking on Wikipedia and Wikidata Inproceedings
In: Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, EACL 2021, Online, April 19 - 23, 2021, pp. 504–514, Association for Computational Linguistics, 2021.
RECON: Relation Extraction using Knowledge Graph Context in a Graph Neural Network Inproceedings
In: WWW '21: The Web Conference 2021, Virtual Event / Ljubljana, Slovenia, April 19-23, 2021, pp. 1673–1685, ACM / IW3C2, 2021.
Knowledge Context for Entity and Relation Linking PhD Thesis
University of Bonn, Germany, 2021.
Evaluating the Impact of Knowledge Graph Context on Entity Disambiguation Models Inproceedings
In: CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, Virtual Event, Ireland, October 19-23, 2020, pp. 2157–2160, ACM, 2020.
Fine-tuning BERT with Focus Words for Explanation Regeneration Inproceedings
In: Proceedings of the Ninth Joint Conference on Lexical and Computational Semantics, * SEM@COLING 2020, Barcelona, Spain (Online), December 12-13, 2020, pp. 125–130, Association for Computational Linguistics, 2020.
Encoding Knowledge Graph Entity Aliases in Attentive Neural Network for Wikidata Entity Linking Inproceedings
In: Web Information Systems Engineering - WISE 2020 - 21st International Conference, Amsterdam, The Netherlands, October 20-24, 2020, Proceedings, Part I, pp. 328–342, Springer, 2020.
Old is Gold: Linguistic Driven Approach for Entity and Relation Linking of Short Text Inproceedings
In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2019, Minneapolis, MN, USA, June 2-7, 2019, Volume 1 (Long and Short Papers), pp. 2336–2346, Association for Computational Linguistics, 2019.
Team SVMrank: Leveraging Feature-rich Support Vector Machines for Ranking Explanations to Elementary Science Questions Inproceedings
In: Proceedings of the Thirteenth Workshop on Graph-Based Methods for Natural Language Processing, TextGraphs@EMNLP 2019, Hong Kong, November 4, 2019, pp. 90–100, Association for Computational Linguistics, 2019.
Matching Natural Language Relations to Knowledge Graph Properties for Question Answering Inproceedings
In: Proceedings of the 13th International Conference on Semantic Systems, SEMANTiCS 2017, Amsterdam, The Netherlands, September 11-14, 2017, pp. 89–96, ACM, 2017.
Capturing Knowledge in Semantically-typed Relational Patterns to Enhance Relation Linking Inproceedings
In: Proceedings of the Knowledge Capture Conference, K-CAP 2017, Austin, TX, USA, December 4-6, 2017, pp. 31:1–31:8, ACM, 2017.