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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..

CAWIML: a computer assisted web interviewing mark-up language. (2016)
Thesis
LLORET PEREZ, J.M. 2016. CAWIML: a computer assisted web interviewing mark-up language. Robert Gordon University, MRes thesis.

Computer-Assisted Web Interviewing (CAWI) is the new mode of conducting surveys through web browsers. This on-line solution extends the traditional paper questionnaire with functionality to inform the order of questions, the logic to guide question r... Read More about CAWIML: a computer assisted web interviewing mark-up language..

Contextual lexicon-based sentiment analysis for social media. (2016)
Thesis
MUHAMMAD, A.B. 2016. Contextual lexicon-based sentiment analysis for social media. Robert Gordon University, PhD thesis.

Sentiment analysis concerns the computational study of opinions expressed in text. Social media domains provide a wealth of opinionated data, thus, creating a greater need for sentiment analysis. Typically, sentiment lexicons that capture term-sentim... Read More about Contextual lexicon-based sentiment analysis for social media..

Contextual sentiment analysis for social media genres. (2016)
Journal Article
MUHAMMAD, A., WIRATUNGA, N. and LOTHIAN, R. 2016. Contextual sentiment analysis for social media genres. Knowledge-based systems [online], 108, pages 92-101. Available from: https://doi.org/10.1016/j.knosys.2016.05.032

The lexicon-based approaches to opinion mining involve the extraction of term polarities from sentiment lexicons and the aggregation of such scores to predict the overall sentiment of a piece of text. It is typically preferred where sentiment labelle... Read More about Contextual sentiment analysis for social media genres..

Survey state model (SSM): XML authoring of electronic questionnaires. (2015)
Conference Proceeding
LLORET, J. and WIRATUNGA, N. 2015. Survey state model (SSM): XML authoring of electronic questionnaires. In Kosek, J. (ed.) XML Prague 2015 conference proceedings. Hájích, Czech Republic: Ing. Jiří Kosek [online], pages 159-178. Available from: https://archive.xmlprague.cz/2015/files/xmlprague-2015-proceedings.pdf

Computer Assisted Interviewing (CAI) systems use questionnaires as the instruments to conduct survey research. XML constitutes a formal way to represent the features of questionnaires which include content coverage, personalisation aspects and import... Read More about Survey state model (SSM): XML authoring of electronic questionnaires..

Hybrid models for combination of visual and textual features in context-based image retrieval. (2013)
Thesis
KALICIAK, L. 2013. Hybrid models for combination of visual and textual features in context-based image retrieval. Robert Gordon University, PhD thesis.

Visual Information Retrieval poses a challenge to intelligent information search systems. This is due to the semantic gap, the difference between human perception (information needs) and the machine representation of multimedia objects. Most existing... Read More about Hybrid models for combination of visual and textual features in context-based image retrieval..

Two-part segmentation of text documents. (2012)
Conference Proceeding
DEEPAK, P., VISWESWARIAH, K., WIRATUNGA, N. and SANI, S. 2012. Two-part segmentation of text documents. In Proceedings of the 21st Association for Computing Machinery (ACM) International conference on information and knowledge management (CIKM'12), 29 October - 02 November 2012, Maui, USA. New York: ACM [online], pages 793-802. Available from: https://dx.doi.org/10.1145/2396761.2396862

We consider the problem of segmenting text documents that have a two-part structure such as a problem part and a solution part. Documents of this genre include incident reports that typically involve description of events relating to a problem follow... Read More about Two-part segmentation of text documents..

A knowledge acquisition tool to assist case authoring from texts. (2009)
Thesis
ASIIMWE, S.M. 2009. A knowledge acquisition tool to assist case authoring from texts. Robert Gordon University, PhD thesis.

Case-Based Reasoning (CBR) is a technique in Artificial Intelligence where a new problem is solved by making use of the solution to a similar past problem situation. People naturally solve problems in this way, without even thinking about it. For exa... Read More about A knowledge acquisition tool to assist case authoring from texts..

Representation and learning schemes for sentiment analysis. (2009)
Thesis
MUKRAS, R. 2009. Representation and learning schemes for sentiment analysis. Robert Gordon University, PhD thesis.

This thesis identifies four novel techniques of improving the performance of sentiment analysis of text systems. Thes include feature extraction and selection, enrichment of the document representation and exploitation of the ordinal structure of rat... Read More about Representation and learning schemes for sentiment analysis..

Automatically acquiring structured case representations: the SMART way. (2008)
Conference Proceeding
ASIIMWE, S., CRAW, S., WIRATUNGA, N. and TAYLOR, B. 2008. Automatically acquiring structured case representations: the SMART way. In Ellis, R., Allen, T. and Petridis, M. (eds.) Applications and innovations in intelligent systems XV: application proceedings of the 27th Annual international conference of the British Computer Society's Specialist Group on Artificial Intelligence (SGAI) (AI-2007): innovative techniques and applications of artificial intelligence, 10-12 December 2007, Cambridge, UK. London: Springer [online], pages 45-58. Available from: https://doi.org/10.1007/978-1-84800-086-5_4

Acquiring case representations from textual sources remains an interesting challenge for CBR research. Approaches based on methods in information retrieval require large amounts of data and typically result in knowledge-poor representations. The cost... Read More about Automatically acquiring structured case representations: the SMART way..

Introspective knowledge acquisition for case retrieval networks in textual case base reasoning. (2007)
Thesis
CHAKRABORTI, S. 2007. Introspective knowledge acquisition for case retrieval networks in textual case base reasoning. Robert Gordon University, PhD thesis.

Textual Case Based Reasoning (TCBR) aims at effective reuse of information contained in unstructured documents. The key advantage of TCBR over traditional Information Retrieval systems is its ability to incorporate domain-specific knowledge to facili... Read More about Introspective knowledge acquisition for case retrieval networks in textual case base reasoning..

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..

Learning adaptation knowledge to improve case-based reasoning. (2006)
Journal Article
CRAW, S., WIRATUNGA, N. and ROWE, R. 2006. Learning adaptation knowledge to improve case-based reasoning. Artificial intelligence, 170(16-17), pages 1175-1192. Available from: https://doi.org/10.1016/j.artint.2006.09.001

Case-Based Reasoning systems retrieve and reuse solutions for previously solved problems that have been encountered and remembered as cases. In some domains, particularly where the problem solving is a classification task, the retrieved solution can... Read More about Learning adaptation knowledge to improve case-based reasoning..

Case-based reasoning for matching SMARTHOUSE technology to people's needs. (2004)
Journal Article
WIRATUNGA, N., CRAW, TAYLOR, B. and DAVIS, G. 2004. Case-based reasoning for matching SMARTHOUSE technology to people's needs. Knowledge-based systems [online], 17 (2-4), pages 139-146. Available from: https://doi.org/10.1016/j.knosys.2004.03.009

SMARTHOUSE technology offers devices that help the elderly and people with disabilities to live independently in their homes. This paper presents our experiences from a pilot project applying case-based reasoning techniques to match the needs of the... Read More about Case-based reasoning for matching SMARTHOUSE technology to people's needs..

Informed selection and use of training examples for knowledge refinement. (2000)
Thesis
WIRATUNGA, N.C. 2000. Informed selection and use of training examples for knowledge refinement. Robert Gordon University, PhD thesis.

Knowledge refinement tools seek to correct faulty rule-based systems by identifying and repairing faults indicated by training examples that provide evidence of faults. This thesis proposes mechanisms that improve the effectiveness and efficiency of... Read More about Informed selection and use of training examples for knowledge refinement..