Computer science Personalised Information Retrieval (PIR)
Catherine Mulwa, Luca Longo, Séamus Lawless, Mary Sharp and Vincent Wade, An Online Framework for Supporting the Evaluation of Personalised Information Retrieval Systems, iUBICOM 11: The 6th International Workshop on Ubiquitous and Collaborative Computing, Northumbria University, 4 July 2011, BCS, 2011, 75-85
Scope - Personalised Information Retrieval (PIR) has been gaining attention because it investigates intelligent ways for enhancing content delivery. Web users can have personalised services and more accurate information. Problem - Several PIR systems have been proposed in the literature; however, they have not been properly tested or evaluated. Proposal - The authors propose a generally applicable web-based interface, which provides PIR developers and evaluators with: i) implicit recommendations on how to evaluate a specific PIR system; ii) a repository containing studies on user-centred and layered evaluation studies; iii) recommendations on how to best combine different evaluation methods, metrics and measurement criteria in order to most effectively evaluate their system; iv) a UCE methodology which details how to apply existing UCE techniques; v) a taxonomy of evaluations of adaptive systems; and vi) interface translation support (49 languages supported).
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