Piotr Przybyła

Natural Language Processing Researcher

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About Me

I am a research fellow at The University of Manchester in the UK, working in the National Centre for Text Mining (NaCTeM) group. I have obtained my PhD degree in Computer Science from the Institute of Computer Science, Polish Academy of Sciences in Warsaw, Poland.

Research

Interests

Machine Learning in NLP

Applying methods of machine learning and statistics to highly-dimensional natural language data.

Question Answering and Text Mining

Extracting valuable knowledge from vast text corpora (especially biomedical scientific literature) to satisfy users' needs.

Author Profiling

Recognising person's background, e.g., gender, age, education, personality, based on a collection of his/her texts.

... and more

image analysis in frequency domain, text classification, NLP of Polish, word sense disambiguation, etc.

Current projects

Publications

Journal Articles

  1. G. Kontonatsios, A. J. Brockmeier, P. Przybyła, J. McNaught, T. Mu, J. Y. Goulermas, S. Ananiadou, “A semi-supervised approach using label propagation to support citation screening,” Journal of Biomedical Informatics, vol. 72, 2017.[bib][paper]
  2. P. Przybyła, M. Shardlow, S. Aubin, R. Bossy, R. Eckart de Castilho, S. Piperidis, J. McNaught, S. Ananiadou, “Text Mining Resources for the Life Sciences,” Database: The Journal of Biological Databases and Curation, vol. 2016, 2016.[bib][paper]
  3. P. Przybyła and P. Teisseyre, “Analysing Utterances in Polish Parliament to Predict Speaker’s Background,” Journal of Quantitative Linguistics, vol. 21, no. 4, pp. 350–376, 2014.[bib][paper]
  4. P. Przybyła, “A pattern recognition method for lattice distortion measurement from HRTEM images,” Journal of Microscopy, vol. 245, no. 2, pp. 200–209, 2011.[bib][paper]

Conference Proceedings

  1. P. Przybyła, N. T. H. Nguyen, M. Shardlow, G. Kontonatsios, and S. Ananiadou, “NaCTeM at SemEval-2016 Task 1: Inferring sentence-level semantic similarity from an ensemble of complementary lexical and sentence-level features,” in Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval 2016), San Diego, USA, 2016.[bib][paper]
  2. P. Przybyła and P. Teisseyre, “What do your look-alikes say about you? Exploiting strong and weak similarities for author profiling - Notebook for PAN at CLEF 2015,” in CLEF 2015 Labs and Workshops, Notebook Papers, Toulouse, France, 2015.[bib][paper][data][corpus]
  3. P. Przybyła, “Gathering Knowledge for Question Answering Beyond Named Entities,” in Proceedings of the 20th International Conference on Applications of Natural Language to Information Systems (NLDB 2015), Passau, Germany, 2015.[bib][paper]
  4. P. Przybyła, “Question Analysis for Polish Question Answering,” in 51st Annual Meeting of the Association for Computational Linguistics, Proceedings of the Student Research Workshop, Sofia, Bulgaria, 2013.[bib][paper]
  5. P. Przybyła, “Question Classification for Polish Question Answering,” in Proceedings of the 20th International Conference on Language Processing and Intelligent Information Systems (LP&IIS 2013), Warsaw, Poland, 2013.[bib][paper]
  6. P. Przybyła, “Issues of Polish Question Answering,” in Proceedings of the first conference “Information Technologies: Research and their Interdisciplinary Applications” (ITRIA 2012), Warsaw, Poland, 2015.[bib][paper]

Presentations

  1. G. Kontonatsios, R. Batista-Navarro, P. Przybyła, and S. Ananiadou, “Text mining methods to support the development of sensitive search strategies in public health reviews,” in Cochrane Colloquium 2016, Seoul, South Korea, 2016.
  2. M. Shardlow, P. Przybyła, R. Batista-Navarro, J. Carter, J. McNaught, and S. Ananiadou, “Facilitating and promoting web annotation with Argo,” in I Annotate 2016, Berlin, Germany, 2016.
  3. P. Przybyła, “OpenMinTeD -- Open Mining Infrastructure for Text and Data,” in 7th Plenary Meeting of Research Data Alliance (RDA) Poster Session, Tokyo, Japan, 2016.

Other

  1. P. Przybyła, “Boosting Question Answering by Deep Entity Recognition,” Manuscript arXiv:1605.08675 [cs.CL], 2016.[bib][paper][data][corpus]
  2. P. Przybyła, “Odpowiadanie na pytania w języku polskim z użyciem głębokiego rozpoznawania nazw,” (Question Answering in Polish using Deep Entity Recognition), PhD thesis in Institute of Computer Science, Polish Academy of Sciences in Warsaw, Poland, 2015.[bib][paper][data][corpus]

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