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Automatic Identification of Research for Systematic Reviews Using Microsoft Academic Graph

A GCTT project that brings together Centre for Behaviour Change and Institute of Education to automatically identify key publications to reduce the time it takes to update systematic reviews

Photographer:	Mr Stefano Gurciullo, Political Science / School of Public Policy © University College London

1 September 2018

Grant


Grant: Grand Challenges Small Grants
Year awarded: 2018-19
Amount awarded: £4,000

Academics 


  • Ailbhe Finnerty, Centre for Behaviour Change
  • James Thomas, Institute of Education   

The main objective of Automatic Identification of Research for Systematic Reviews Using Microsoft Academic Graph is to develop a method to automatically sort newly published literature into groups of papers that potentially belong in the same systematic review, using data from Microsoft Academic Knowledge or 'Graph'.

The aim is to use the data from Microsoft Academic Graph to determine the features that can be used to identify similarities between publications, which can be applied to all future published papers, this will address a key weakness in the length of time it takes to search and identify relevant publications for inclusion within a systematic review. By attempting to automate this task we hope to make it more efficient and make it possible to keep systematic reviews up to date. 

Outputs and Impacts


  • Awaiting outputs and impacts