Citizen participation and machine learning for a better democracy
Friday 07 Feb 2020
Time: 13:00 - 18:00
Search
Information retrieval
Computational archival science (CAS) symposium
Monday 20 Jan 2020
Time: 09:30 - 17:00
Projects
Trustworthy Digital Infrastructure for Identity Systems
Enhancing the privacy and security of national digital identity systems
CROP: the Crop Research Observation Platform
A prototype digital twin of the Growing Underground underground farm operated by Zero Carbon Farms Ltd
Data science for climate resilience in East Africa
Combining satellite and social data to measure and grow the impact of tree planting schemes in East Africa
Citizen participation and machine learning for a better democracy
Using machine learning and natural language processing to overcome information overload in citizen participation platforms
Analysing humanities books and newspapers data
Text analysis using Cray's supercomputing analytics platform Urika-GX
The data science of music
Applying data science and AI to music analysis and the lifecycle of musical works
From field data to global indicators
Investigating how plant data can be efficiently and reliably linked across data infrastructures around the world
Publications and software
Machines in the media: semantic change in the lexicon of mechanization in 19th-century British newspapers
The industrialisation process associated with the so-called Industrial Revolution in 19th - century Great...
Proceedings of the 2nd International Workshop on Natural Language Processing for Digital Humanities, pages 85–95, Taipei, Taiwan. Association for Computational Linguistics.
Design choices for productive, secure, data-intensive research at scale in the cloud
We present a policy and process framework for secure environments for productive data science...
Arenas, Diego & Atkins, Jon & Austin, Clare & Beavan, David & Cabrejas Egea, Alvaro & Carlysle-Davies, Stephen & Carter, Ian & Clarke, Rob & Cunningham, James & Doel, Tom & Forrest, Oliver & Gabasova, Evelina & Geddes, James & Hetherington, James & Jersakova, Radka & Kiraly, Franz & Lawrence, Catherine & Manser, Jules & O'Reilly, Martin & Whitaker, Kirstie. (2019). Design choices for productive, secure, data-intensive research at scale in the cloud. arXiv:1908.08737 [cs.CR]
Mining the UK Web Archive for Semantic Change Detection
Semantic change detection (i.e., identifying words whose meaning has changed over time) started emerging...
Tsakalidis, A., Bazzi, M., Cucuringu, M., Basile, P., & McGillivray, B. Mining the UK Web Archive for Semantic Change Detection. Proceedings of INTERNATIONAL CONFERENCE RECENT ADVANCES IN NATURAL LANGUAGE PROCESSING, https://doi.org/10.17863/CAM.43534
Wrangling Messy CSV Files by Detecting Row and Type Patterns
Data scientists spend the majority of their time on preparing data for analysis. One...
Van den Burg, G. J. J., Nazabal, A., and Sutton, C. (2019). Wrangling messy CSV files by detecting row and type patterns. Data Mining and Knowledge Discovery, 33(6), pp. 1799-1820.
Events
Citizen participation and machine learning for a better democracy
Friday 07 Feb 2020
Time: 13:00 - 18:00
Computational archival science (CAS) symposium
Monday 20 Jan 2020
Time: 09:30 - 17:00
Interest groups
Interpretation, modelling and verification of information
How data science and artificial intelligence help people understand/handle information correctly?
Machine learning for radio frequency applications
How do we generate robust, real-time machine learning algorithms with integrated hardware and software for radio frequency applications?
People
Professor Jon Crowcroft
Researcher at Large
Wei Nie
Enrichment Student
Amin Mekacher
Enrichment Student
Berker Banar
Enrichment Student
Jennifer Sykes
Enrichment Student
Russell Martin
Enrichment Student
Victoria Smith
Enrichment Student
Timothy Sum Hon Mun
Enrichment Student