The Big Data Institute at University College London

  • Gower St

    WC1E 6BT London

    United Kingdom

Organization profile

Organization Profile

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.

The research undertaken through the Big Data Institute forms part of the broader activities of the UCL Centre for Data Science. For UCL's data science-related news and events, visit the Centre for Data Science Website.

'Big Data' is a general term, referring to the huge volumes and varieties of data which have become ubiquitous in government, society and science. 

Fingerprint Dive into the research topics where The Big Data Institute at University College London is active. These topic labels come from the works of this organization's members. Together they form a unique fingerprint.

  • Projects

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

    Lunagomez, S., Collins, E., Augenstein, I., Riedel, S., Maynard, D., Montcheva, K., Ling, E. & Hobby, M.

    10/1/1509/30/17

    Project: Research

    Dynamic User Interests

    Liang, S., Ren, Z., Zhao, Y., Yilmaz, E., Kanoulas, E., Ma, J., De Rijke, M. & Hobby, M.

    08/1/1507/1/19

    Project: Research

    Research Output

    Collaboratively Tracking Interests for User Clustering in Streams of Short Texts

    Liang, S., Yilmaz, E. & Kanoulas, E., 2018, IEEE Transactions on Knowledge and Data Engineering.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • 6 Scopus citations

    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 contribution

    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 contribution

    9 Scopus citations

    Press / Media

    These Elsevier collaborations use machine learning to turn data into knowledge

    Tim Menzies, Karin Verspoor, David Jones, Anne Gabriel, George Tsatsaronis & Lesley Thompson

    12/1/17

    1 Media contribution

    Press/Media