Miriam Fernandez PROFILE PHOTO

My current research at KMi is focused on the analysis of online communities (Social Web). My aim is to understand users' behaviour and needs and to develop prediction models to foreseen risks and opportunities in online communities based on the behaviour of their users. I have also previously worked on semantic Search. Within the context of this research line I investigated methods to enhance traditional IR and QA techniques introducing higher level of conceptualisations in the form of ontologies as well as methods and benchmarks to evaluate semantic search systems


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KMi at K-Cap2017

KMi continued its long association with the KAW/K-CAP series of workshops and conferences this week with a strong presence at the 9th International Conference on Knowledge Capture(K-CAP2017) held in Austin, Texas, USA the first week of December....Read more

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KMi at ISWC 2017

It was the turn of Vienna, Austria to host the International Semantic Web Conference, and once again KMi’s participation at the event was very strong....Read more

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Development of filmic representations of social media content for individuals and groups using a mixture of semantic, content, and network analysis...Read more

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tools and techniques to enable policy makers to gather, integrate, and analyse policy-related discussions...Read more

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A Decarbonisation Platform for Citizen Empowerment and Translating Collective Awareness into Behavioural Change...Read more

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ROBUST aims to analyze, manage and care for online communities to support their well being & to measure their created value....Read more

Dickinson, T., Fernandez, M., Thomas, L, Mulholland, P., Briggs, P and Alani, H. (2016) Detecting Important Life Events on Twitter Using Frequent Semantic and Syntactic Subgraphs, IADIS International Journal on WWW/Internet, 14, 2, pp. 23-37

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Knowledge Media Institute
The Open University
Milton Keynes
United Kingdom

+44 (0)1908 659400