https://www.ucl.ac.uk/data-science/ucl-big-data-institute

  • 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. 

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    • 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.

    10/1/15 → 09/30/17

    Project: Research

    Dynamic User Interests

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

    08/1/15 → 07/1/19

    Project: Research

    Predicting Functionality of Novel Proteins with University College London

    Jones, D. & Thompson, L.

    11/1/14 → 01/1/18

    Project: Research

    Research Output

    • 6 Article
    • 3 Conference contribution
    • 3 Paper

    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 proceeding › Conference contribution

    • 4 Scopus citations

    A Concept Language Model for Ad-Hoc Search.

    Zou, B., Lampos, V., Liang, S., Ren, Z., Yilmaz, E. & Cox, I., 2017, In : WWW '17 Companion Proceedings of the 26th International Conference on World Wide Web Companion. p. 885-886

    Research output: Contribution to journal › Article

    • 2 Scopus citations

    A Supervised Approach to Extractive Summarisation of Scientific Papers

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

    Research output: Contribution to conference › Paper