Research

Personalisation is a concept behind systems such as recommender (my learning) where human collaboration is significant. Personalisation will optimise the user experience in the recommender systems. This research focuses the service level optimisation where web services are collaborating.
Current Semantic web can be easily described by Description Logic (DL) . My effort was to use of the DL to personalise web services. DL can be used to express the Semantic web languages such as OWL-DL which I used the proof of concept explained in the following publications.

Thesis

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The research theme is personalisation. As a result of my findings, I realised DL could be the right solution to personalise web services. In my research thesis, the semantic way of selecting the best suitable web service from very similar services has explained. The solution is catering for the user preferences, but that should be ontology-based (instead of traditional machine learning): this is where Semantic Web come to play. I would like to share the publications I’ve presented for the international IEEE conferences:

Publications

Conference: IEEE ICIIS 2006
Ojitha Kumanayaka and Nalin Ranasinghe. Personalised web services creation via dynamic composition. In IEEE First International Conference on Industrial and Information Systems. Faculty of Engineering, University of Peradeniya, August 2006. Read more …

Conference: IEEE ICIA 2006
Ojitha Kumanayaka and Nalin Ranasinghe. Ontology-based web service personalisation. In IEEE Second International Conference on Information and Automation 2006, Galadari Hotel and Colombo and Sri Lanka, December 2006. IEEE Sri Lanka Section. Read more …

Conference: IEEE ICIIS 2007
Ojitha Kumanayaka and Nalin Ranasinghe. Formalism for ontology validation. In IEEE Second International Conference on Industrial and Information Systems. Faculty of Engineering, University of Peradeniya, August 2007. Read more …

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