Personalisation is an important area in the field of IR that attempts to adapt ranking algorithms so that the results returned are tuned towards the searcher's interests. In this work we use query logs to build personalised ranking models in which user profiles are constructed based on the representation of clicked documents over a topic space. Instead of employing a human-generated ontology, we use novel latent topic models to determine these topics. Our experiments show that by subtly introducing user profiles as part of the ranking algorithm, rather than by re-ranking an existing list, we can provide personalised ranked lists of documents which improve significantly over a non-personalised baseline. Further examination shows that the performance of the personalised system is particularly good in cases where prior knowledge of the search query is limited.

Food recommenders have been touted as a useful tool to help people achieve a healthy diet. Here we incorporate nutrition into the recommender problem by examining the feasibility of algorithmically creating daily meal plans for a sample of user profiles (n=100), combined with a diverse set of food preference data (n=64) collected in a natural setting. Our analyses demonstrate it is possible to recommend plans for a large percentage of users which meet the guidelines set out by international health agencies

This study investigates the issue of digital exclusion resulting from the digitisation of government and council services within the United Kingdom. An initial analysis of customer support log data from a council in a large UK city helped identify the most commonly queried services and modes of support. The main findings are based on qualitative analysis of 10 interviews, structured around the results from the log analysis, conducted with front-line staff members at the central library of the same council. The study identifies a range of issues associated with the provision of e-government services and the subsequent under-utilisation by the public, including poor design, issues with effective access and the level of digital literacy among end users. The study also proposes the concept of the ‘digital carer’, a friend or family member who is relied upon by users unable to interact with e-government services themselves. The findings of this study have implications for the way in which these services are designed and delivered and point to the need for further work that can contribute to the UK digital economy by facilitating better access to e-government services and reduce digital exclusion, especially for elderly and marginalised users.