Construction of Method and Algorithm Knowledge Graphs at University College London (UCL) Big Data Institute

  • Lunagomez, Simon (CoI)
  • Collins, Ed (CoI)
  • Augenstein, Isabelle (CoI)
  • Riedel, Sebastian (CoI)
  • Maynard, Diana (CoI)
  • Montcheva, Kalina (CoI)
  • Ling, Elisabeth (CoI)
  • Hobby, Matt (CoI)

Project Details


The UCL Big Data Institute explores innovative ways to better serve the needs of researchers, through the investigation of new technologies and analytics as applied to scholarly content and data.

The Institute is an innovation hub, based at UCL, founded with support from Elsevier. It tackles the challenges faced by researchers as they seek to forecast trends, synthesise information from thousands of research papers and show the potential societal impact of their research.
Effective start/end date10/1/1509/30/17


Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.
  • Jack the Reader - A machine reading framework

    Weissenborn, D., Minervini, P., Dettmers, T., Augenstein, I., Johannes Welb, J., Rocktaeschel, T., Bosnjak, M. & Mitchell, J., 2018, ACL 2018 - 56th Annual Meeting of the Association for Computational Linguistics, Proceedings of System Demonstration.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

  • Ranking-based Method for News Stance Detection

    Zhang, Q., Yilmaz, E. & Liang, S., 2018, The Web Conference 2018 - Companion of the World Wide Web Conference, WWW 2018.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    18 Scopus citations
  • A Supervised Approach to Extractive Summarisation of Scientific Papers

    Collins, E., Augenstein, I. & Riedel, S., Jul 1 2017.

    Research output: Contribution to conferencePaperpeer-review

    21 Scopus citations