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mHealth optimisation for education and physical activity in Type 1 diabetes: MEDPAT1. (2017)
Presentation / Conference
HALL, J., STEPHEN, K., CROALL, A., MACMILLAN, J., MURRAY, L., WIRATUNGA, N., MASSIE, S. and MACRURY, S. 2017. mHealth optimisation for education and physical activity in Type 1 diabetes: MEDPAT1. Presented at the 2017 Diabetes UK professional conference, 8-10 March 2017, Manchester, UK.

Aims: To develop and evaluate usability of prototype personalised prediction algorithms for people with Type 1 diabetes to optimise blood glucose control associated with physical activity using smart phone technology. To explore the potential to buil... Read More about mHealth optimisation for education and physical activity in Type 1 diabetes: MEDPAT1..

Lexicon generation for emotion detection from text. (2017)
Journal Article
BANDHAKAVI, A., WIRATUNGA, N., MASSIE, S. and PADMANABHAN, D. 2017. Lexicon generation for emotion detection from text. IEEE intelligent systems [online], 32(1), pages 102-108. Available from: https://doi.org/10.1109/MIS.2017.22

General-purpose emotion lexicons (GPELs) that associate words with emotion categories remain a valuable resource for emotion detection. However, the static and formal nature of their vocabularies make them an inadequate resource for detecting emotion... Read More about Lexicon generation for emotion detection from text..

Lexicon based feature extraction for emotion text classification. (2016)
Journal Article
BANDHAKAVI, A., WIRATUNGA, N., DEEPAK, P. and MASSIE, S. 2017. Lexicon based feature extraction for emotion text classification. Pattern recognition letters [online], 93, pages 133-142. Available from: https://doi.org/10.1016/j.patrec.2016.12.009

General Purpose Emotion Lexicons (GPELs) that associate words with emotion categories remain a valuable resource for emotion analysis of text. However the static and formal nature of their vocabularies make them inadequate for extracting effective fe... Read More about Lexicon based feature extraction for emotion text classification..

SelfBACK: Activity recognition for self-management of low back pain. (2016)
Conference Proceeding
SANI, S., WIRATUNGA, N., MASSIE, S. and COOPER, K. 2016. SelfBACK: Activity recognition for self-management of low back pain. In Bramer, M. and Petridis, M. (eds.) 2016. Research and development in intelligent systems XXXIII: incorporating applications and innovations in intelligent systems XXIV: proceedings of the 36th SGAI nternational conference on innovative techniques and applications of artificial intelligence (SGAI 2016), 13-15 December 2016, Cambridge, UK. Cham: Springer [online], pages 281-294. Available from: https://doi.org/10.1007/978-3-319-47175-4_21

Low back pain (LBP) is the most significant contributor to years lived with disability in Europe and results in significant financial cost to European economies. Guidelines for the management of LBP have self-management at their cornerstone, where pa... Read More about SelfBACK: Activity recognition for self-management of low back pain..

Emotion-corpus guided lexicons for sentiment analysis on Twitter. (2016)
Conference Proceeding
BANDHAKAVI, A., WIRATUNGA, N. and MASSIE, S. 2016. Emotion-corpus guided lexicons for sentiment analysis on Twitter. In Bramer, M. and Petridis, M. (eds.) 2016. Research and development in intelligent systems XXXIII: incorporating applications and innovations in intelligent systems XXIV: proceedings of the 36th SGAI nternational conference on innovative techniques and applications of artificial intelligence (SGAI 2016), 13-15 December 2016, Cambridge, UK. Cham: Springer [online], pages 71-86. Available from: https://doi.org/10.10007/978-3-319-47175-4_5

Research in Psychology have proposed frameworks that map emotion concepts with sentiment concepts. In this paper we study this mapping from a computational modelling perspective with a view to establish the role of an emotion-rich corpus for lexicon-... Read More about Emotion-corpus guided lexicons for sentiment analysis on Twitter..

Harnessing background knowledge for e-learning recommendation. (2016)
Conference Proceeding
MBIPOM, B., CRAW, S. and MASSIE, S. 2016. Harnessing background knowledge for e-learning recommendation. In Bramer, M. and Petridis, M. (eds.) 2016. Research and development in intelligent systems XXXIII: incorporating applications and innovations in intelligent systems XXIV: proceedings of the 36th SGAI nternational conference on innovative techniques and applications of artificial intelligence (SGAI 2016), 13-15 December 2016, Cambridge, UK. Cham: Springer [online], pages 3-17. Available from: https://dx.doi.org/10.1007/978-3-319-47175-4_1

The growing availability of good quality, learning-focused content on the Web makes it an excellent source of resources for e-learning systems. However, learners can find it hard to retrieve material well-aligned with their learning goals because of... Read More about Harnessing background knowledge for e-learning recommendation..

Music recommendation: audio neighbourhoods to discover music in the long tail. (2015)
Conference Proceeding
CRAW, S., HORSBURGH, B. and MASSIE, S. 2015. Music recommendation: audio neighbourhoods to discover music in the long tail. In Hüllermeier, E. and Minor, M. (eds.) Proceedings of the 23rd international conference on case-based reasoning research and development (ICCBR 2015), 28-30 September 2015, Frankfurt am Main, Germany. Lecture notes in computer science, 9343. Cham: Springer [online], pages 73-87. Available from: https://doi.org/10.1007/978-3-319-24586-7_6

Millions of people use online music services every day and recommender systems are essential to browse these music collections. Users are looking for high quality recommendations, but also want to discover tracks and artists that they do not already... Read More about Music recommendation: audio neighbourhoods to discover music in the long tail..

Case-base maintenance with multi-objective evolutionary algorithms. (2015)
Journal Article
LUPIANI, E., MASSIE, S., CRAW, S., JUAREZ, J.M. and PALMA, J. 2016. Case-base maintenance with multi-objective evolutionary algorithms. Journal of intelligent information systems [online], 46(2), pages 259-284. Available from: https://doi.org/10.1007/s10844-015-0378-z

Case-Base Reasoning is a problem-solving methodology that uses old solved problems, called cases, to solve new problems. The case-base is the knowledge source where the cases are stored, and the amount of stored cases is critical to the problem-solvi... Read More about Case-base maintenance with multi-objective evolutionary algorithms..

Music recommenders: user evaluation without real users? (2015)
Conference Proceeding
CRAW, S., HORSBURGH, B. and MASSIE, S. 2015. Music recommenders: user evaluation without real users? In Yang, Q. and Woolridge, M. (eds.) Proceedings of the 24th International joint conference on artificial intelligence (IJCAI-15), 25-31 July 2015, Buenos Aires, Argentina. Palo Alto: AAAI Press [online], pages 1749-1755. Available from: https://www.ijcai.org/Proceedings/15/Papers/249.pdf

Good music recommenders should not only suggest quality recommendations, but should also allow users to discover new/niche music. User studies capture explicit feedback on recommendation quality and novelty, but can be expensive, and may have difficu... Read More about Music recommenders: user evaluation without real users?.

Learning pseudo-tags to augment sparse tagging in hybrid music recommender systems. (2014)
Journal Article
HORSBURGH, B., CRAW, S. and MASSIE, S. 2015. Learning pseudo-tags to augment sparse tagging in hybrid music recommender systems. Artificial intelligence [online], 219, pages 25-39. Available from: https://doi.org/10.1016/j.artint.2014.11.004

Online recommender systems are an important tool that people use to find new music. To generate recommendations, many systems rely on tag representations of music. Such systems however suffer from tag sparsity, whereby tracks lack a strong tag repres... Read More about Learning pseudo-tags to augment sparse tagging in hybrid music recommender systems..

Role of semantic indexing for text classification. (2014)
Thesis
SANI, S. 2014. Role of semantic indexing for text classification. Robert Gordon University, PhD thesis.

The Vector Space Model (VSM) of text representation suffers a number of limitations for text classification. Firstly, the VSM is based on the Bag-Of-Words (BOW) assumption where terms from the indexing vocabulary are treated independently of one anot... Read More about Role of semantic indexing for text classification..

A multi-objective evolutionary algorithm fitness function for case-base maintenance. (2013)
Conference Proceeding
LUPIANI, E., CRAW, S., MASSIE, S., JUAREZ, J.M. and PALMA, J.T. 2013. A multi-objective evolutionary algorithm fitness function for case-base maintenance. In Delany, S.J. and Ontañón, S. (eds.) Case-based reasoning research and development: proceedings of the 21st International conference on case-based reasoning (ICCBR 2013), 8-11 July 2013, Saratoga Springs, USA. Lecture notes in computer science, 7969. Berlin: Springer [online], pages 218-232. Available from: https://doi.org/10.1007/978-3-642-39056-2_16

Case-Base Maintenance (CBM) has two important goals. On the one hand, it aims to reduce the size of the case-base. On the other hand, it has to improve the accuracy of the CBR system. CBM can be represented as a multi-objective optimization problem t... Read More about A multi-objective evolutionary algorithm fitness function for case-base maintenance..

Integrating content and semantic representations for music recommendation. (2013)
Thesis
HORSBURGH, B. 2013. Integrating content and semantic representations for music recommendation. Robert Gordon University, PhD thesis.

Music recommender systems are used by millions of people every day to discover new and exciting music. Central to making recommendations is the representation of each track, which may be used to calculate similarity. Content representations capture t... Read More about Integrating content and semantic representations for music recommendation..

Cold-start music recommendation using a hybrid representation. (2012)
Presentation / Conference
HORSBURGH, B., CRAW, S. and MASSIE, S. 2012. Cold-start music recommendation using a hybrid representation. Presented at the 3rd Annual digital economy 'all hands' conference (Digital Futures 2012), 23-25 October 2012, Aberdeen, UK.

Digital music systems are a new and exciting way to dis- cover, share, and listen to new music. Their success is so great, that digital downloads are now included alongside tra- ditional record sales in many o cial music charts [10]. In the past list... Read More about Cold-start music recommendation using a hybrid representation..

Music-inspired texture representation. (2012)
Conference Proceeding
HORSBURGH, B., CRAW, S. and MASSIE, S. 2012. Music-inspired texture representation. In Proceedings of the 26th Association for the Advancement of Artificial Intelligence conference on artificial intelligence (AAAI-12), co-located with the 2012 Symposium on educational advances in artificial intelligence (EAAI-12), 22-26 July 2012, Toronto, Canada. Palo Alto: AAAI Press [online], pages 52-58. Available from: https://www.aaai.org/ocs/index.php/AAAI/AAAI12/paper/view/5041

Techniques for music recommendation are increasingly relying on hybrid representations to retrieve new and exciting music. A key component of these representations is musical content, with texture being the most widely used feature. Current technique... Read More about Music-inspired texture representation..

Finding the hidden gems: recommending untagged music. (2011)
Conference Proceeding
HORSBURGH, B., CRAW, S., MASSIE, S. and BOSWELL, R. 2011. Finding the hidden gems: recommending untagged music. In Proceedings of the 22nd International joint conference on artificial intelligence (IJCAI-11), 16-22 July 2011, Barcelona, Spain. Palo Alto: AAAI Press [online], pages 2256-2261. Available from: https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-376

We have developed a novel hybrid representation for Music Information Retrieval. Our representation is built by incorporating audio content into the tag space in a tag-track matrix, and then learning hybrid concepts using latent semantic analysis. We... Read More about Finding the hidden gems: recommending untagged music..

Plan recommendation for well engineering. (2011)
Conference Proceeding
THOMSON, R., MASSIE, S., CRAW, S., AHRIZ, H. and MILLS, I. 2011. Plan recommendation for well engineering. In Mehrotra, K.G., Mohan, C.K., Oh, J.C., Varshney, P.K. and Ali, M. (eds.) Modern approaches in applied intelligence: proceedings of the 24th International conference on industrial, engineering and other applications of applied intelligent systems (IEA/AIE 2011), 28 June - 1 July 2011, Syracuse, USA. Lecture notes in computer science, 6704. Berlin: Springer [online], part II, pages 436-445. Available from: https://doi.org/10.1007/978-3-642-21827-9_45

Good project planning provides the basis for successful offshore well drilling projects. In this domain, planning occurs in two phases: an onshore phase develops a project plan; and an offshore phase implements the plan and tracks progress. The Perfo... Read More about Plan recommendation for well engineering..

Complexity modelling for case knowledge maintenance in case-based reasoning. (2006)
Thesis
MASSIE. S. 2006. Complexity modelling for case knowledge maintenance in case-based reasoning. Robert Gordon University, PhD thesis.

Case-based reasoning solves new problems by re-using the solutions of previously solved similar problems and is popular because many of the knowledge engineering demands of conventional knowledge-based systems are removed. The content of the case kno... Read More about Complexity modelling for case knowledge maintenance in case-based reasoning..

A case-based approach to data-to-text generation. [Software]
Digital Artefact
UPADHYAY, A., MASSIE, S., SINGH, R.K., GUPTA, G. and OJHA, M. 2021. A case-based approach to data-to-text generation. [Software]. Hosted on GitHub [online]. Available from: https://github.com/ashishu007/data2text-cbr

Traditional Data-to-Text Generation (D2T) systems utilise carefully crafted domain specific rules and templates to generate high quality accurate texts. More recent approaches use neural systems to learn domain rules from the training data to produce... Read More about A case-based approach to data-to-text generation. [Software].