Stewart Massie Profile2
Title: Dr
First Name: Stewart
Surname: Massie
Position: Reader
Telephone: +44 (0) 1224 262570


Stewart is a Senior Research Fellow at Robert Gordon University working with the Smart Information Systems group in the School of Computing Science and Digital Media. His research in Artificial Intelligence develops improved technologies for data mining with a focus on Case-Based Reasoning and Recommender Systems. He received his PhD from RGU in 2006. Previously, he has worked on software development projects with Atlantic Bow (Edinburgh); and on engineering research & development projects with Johnson Matthey (London), International Twist Drill Ltd (Aberdeen) and SPIMACo (Saudi Arabia).

Duties and Responsibilities

  • Active researcher in Case-Based Reasoning, Recommendation, Data/Text Mining, and Knowledge Discovery
  • Research student supervisor
  • Current Teaching: Enterprise Web Systems (CM4025)

Academic Background

  • PhD in Computing (Complexity Modelling for Case Knowledge in Case-Based Reasoning), Robert Gordon University (2006)
  • MSc. Computing, Robert Gordon University (2002)
  • MEng. Manufacturing Sciences & Engineering, University of Strathclyde 

Research Interests

His current research fits into four broad themes: personalisation & recommendation; knowledge discovery & representation; reasoning from past experiences; and visualisation techniques in decision support. Recent funded projects have focused on recommendation to provide personalised location-aware information to visitors at tourist sites. Previously, in work on knowledge discovery, automated knowledge engineering tools were developed for case-based reasoning (CBR) applications. For example, a novel complexity-based competence model is utilised within a set of CBR tools for case maintenance and discovery. Where experiences are captured in text, feature selection and extraction techniques have been applied using introspective learning approaches, such as latent and propositional semantic indexing, to create representation for textual documents. Applied to other multimedia, such as music and images, hybrid representations capturing content, semantic tags and user interactions have been developed. Novel visualisation techniques have been created that explain the CBR retrieval process by highlighting features that contribute to similarity & differences, and also for visualising the case base to support knowledge maintenance techniques.

Some Recent Projects

  • Music Recommenders: Users of on-line music services are looking for good recommendations, but also want to discover music that they do not already know. This recommender uses audio and social tagging to find tracks that balance novelty with quality.
  • Decisions from Data: a methodology allowing knowledge to be extracted from numeric or textual data, so that it can be effectively retrieved and reused to support decision-making on new problems.
  • Living History: A mobile app solution for tourists improves the interaction with objects at remote historic sites. NFC tags for tap-and-go services provide relevant visitor information about specific objects/places on historic sites to the visitor’s mobile without 3G/Web connectivity.
  • Smart Beacons: This mobile app uses proximity-aware Neate Beacon sensors to trigger the delivery of content relevant to a nearby item. Museums are interested to exploit this to enhance visitor experiences through engagement with exhibits.


Selected grants:

  • EU Horizon2020 - “selfBACK: Decision Support for Self-Management of Lower Back Pain”, Wiratunga, Cooper & Massie, 2015 -2019. Collaborators: NTNU, University of Glasgow, Kiolis France, Det Nationale Forsknings Centre for Arbejdsmiljo, Health Leads Netherlands and Syddansk Universitet
  • SFC Horizon - Smart Tourism funded innovation project “Living History Interactions”, Craw & Massie, 2014.
  • SFC Horizon - Smart Tourism funded innovation project “Smart Beacons”, Massie & Craw, 2013.
  • SFC Horizon - Smart Tourism funded innovation project “Living History”, Craw & Massie, 2012.
  • EPSRC/DTI – KTP funded “Intelligent Project Planning Tool for Well Engineering Projects”, Craw, Ahriz & Massie, 2009-2011.
  • EPSRC/DTI - KTP funded “CBR for Remote Patient Health-Care Monitoring”, Wiratunga, Massie & Craw, 2007-2009. 

External / Professional Roles

  • International expert for SFI EXPOSED Aquaculture Centre for Research-Based Innovation, Trondheim 
  • PC Member of ICCBR and KSEM


Stewart Massie has published over 40 peer-reviewed papers in leading journals and conferences, such as Artificial Intelligence, IJCAI and AAAI (Google Scholar Profile).

Selected publications:

  1. S Craw, B Horsburgh & S Massie (2015). Music recommendation: Audio Neighbourhoods to Discover Music in the Long Tail. Proc. of the 23rd International Conference on Case-Based Reasoning, pages 73–87. Springer Best Paper Award.
  2. E Lupiani, S Craw, S Massie, J M Juarez, J T Palma (2015). Case-base maintenance with multi-objective evolutionary algorithms. Journal of Intelligent Information Systems, Springer.
  3. B Horsburgh, S Craw & S Massie (2015) Music recommenders: user evaluation without real users? Proc. of the 24th Int. Joint Conf. in Artificial Intelligence, pages 1749–1755. AAAI Press.
  4. B Horsburgh, S Craw & S Massie (2015) Learning pseudo-tags to augment sparse tagging in hybrid music recommender systems. Artificial Intelligence 219:25-39. 
  5. Brownlee, Regnier-Coudert, McCall, Massie & Stulajter (2013): An application of a GA with Markov network surrogate to feature selection, International Journal of Systems Science, 44 (11), 2039-2056 
  6. B Horsburgh, S Craw and S Massie (2012) Music-Inspired Texture Representation. In Proceedings of the 26th AAAI Conference on Artificial Intelligence, pages 52-58, Toronto, Canada, AAAI Press.
  7. B Horsburgh, S Craw and S Massie (2011) Finding the hidden gems: Recommending untagged music. In Proceedings of the 22nd Int Joint Conference in Artificial Intelligence (IJCAI), pages 2256–2261, Barcelona, Spain, 2011, AAAI Press. 
  8. Jayanthi, Chakraborti, & Massie (2010) Introspective Knowledge Revision in Textual Case-Based Reasoning. In Proceedings of the 18th Int. Conference on CBR, pages 171–185. Springer
  9. Massie, Wiratunga, Craw, Donati, & Vicari (2007) From anomaly reports to cases. In Proceedings of the 7th Int. Conference on CBR, pages 359–373. Springer
  10. Massie, Craw & Wiratunga (2005) Complexity-guided case discovery for case-based reasoning. Proceedings of the 20th AAAI Conference on Artificial Intelligence: pages 216–221, AAAI Press.