Robert E. Mercer

photo of Dr Mercer.

Professor Emeritus

Office: Middlesex College 28A-2
Tel: 519-661-2111 ext. 86893
Email:mercer@csd.uwo.ca

Personal Web Page


My research interests have included developing various knowledge representation frameworks and schemes and their associated reasoning mechanisms, and applying these processes together with machine learning to natural language, computer vision, animation, human-computer interaction, and information retrieval and information extraction.

My current research focus is argumentation in scholarly biomedical texts. Scientists and clinicians use argumentation to convince readers of their journal papers that the claims made in those papers should become part of the knowledge about biomedicine. Research in my lab is providing methods to have computers find these arguments in the natural language text of journal articles. Outcomes of this research will include indexing of scientific claims and evidence in the research literature, thus providing a method to navigate the scientific literature that adds a new dimension to the presently available keyword searching techniques.

 

Research Interests

Principal Areas: Artificial Intelligence: Computational Linguistics, Natural Language Processing, Argumentation Mining, Logics for Knowledge Representation and Reasoning

Secondary Areas: Applications of Artificial Intelligence: Text Mining, Information Retrieval, Semantic Search, Bioinformatics, Meteorology

Selected Publications

  1. Moser, E. and R. E. Mercer, “Use of claim graphing and argumentation schemes in biomedical literature: A manual approach to analysis”, Proceedings of the 7th Workshop on Argument Mining, pp 88–99, 2020.
  2. Roy, S. S., R. E. Mercer and F. Urra, “Investigating citation linkage as a sentence similarity measurement task using deep learning”, Proceedings of the 33rd Canadian Conference on Artificial Intelligence, pp 483–495, 2020
  3. Ahmed, M., C. Dixit, R. E. Mercer, A. Khan, R. Samee, and F. Urra, Multilingual corpus creation for multilingual semantic similarity task”, Proceedings of the 12th International Conference on Language Resources and Evaluation (LREC 2020), pp 4190–4196, 2020.
  4. Ahmed, M. and R. E. Mercer, “Modelling sentence pairs via reinforcement learning: An Actor-Critic approach to learn the irrelevant words”, Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI 2020), pp 7358–7366, 2020.
  5. Alliheedi, M., Wang, Y., and R. E. Mercer, “Biochemistry procedure-oriented ontology: A case study”, Proceedings of the 11th International Conference on Knowledge Engineering and Ontology Development (KEOD 2019) – Volume 2 of Proceedings of the 11th International Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019), pp 164–173, 2019.
  6. Wang, X. and R. E. Mercer, “Incorporating figure captions and descriptive text in MeSH term indexing”, Proceedings of the BioNLP 2019 Workshop, pp 165–175, 2019.
  7. Ahmed, M. and R. E. Mercer, “Efficient Transformer-based sentence encoding for sentence pair modelling”, Proceedings of the 32nd Canadian Conference on Artificial Intelligence (AI’2019), pp 146–159, 2019. (*** Best student paper of the conference award. ***)
  8. Ahmed, M., M. R. Samee, and R. E. Mercer, “Improving Tree-LSTM with tree attention”, Proceedings of the 2019 IEEE 13th International Conference on Semantic Computing (ICSC), pp 247–254, 2019. (*** Best paper of the conference award. ***) (*** Best student paper of the conference award. ***)
  9. Ahmed, M., J. Islam, M. R. Samee, and R. E. Mercer, “Identifying protein-protein interaction using tree LSTM and structured attention”, Proceedings of the 2019 IEEE 13th International Conference on Semantic Computing (ICSC), pp 224–231, 2019. (*** Nominated for best paper/best student paper of the conference award. ***)
  10. Islam, J., R.E. Mercer, and L. Xiao,“Multi-channel convolutional neural network for Twitter emotion and sentiment recognition”, Proceedings of the North American Chapter of the Association for Computational Linguistics, (NAACL-HLT-2019), pp 1355–1365, 2019.

Awards

  • Vector Institute Emeritus Faculty Affiliate, 2020–present
  • Vector Institute Faculty Affiliate, 2018–2020
  • CAIAC Fellow, 2012
  • CAIAC Distinguished Service Award, 2012
  • Nominated for Faculty of Science Distinguished Research Professorship, 2005
  • Interdisciplinary Chair of Cognitive Science, University of Potsdam, June, 2000
  • Nominated for Faculty of Science Award of Excellence in Undergraduate Teaching, 2000