User evaluation of a market-based recommender system

Recommender systems have been developed for a wide variety of applications (ranging from books, to holidays, to web pages). These systems have used a number of different approaches, since no one technique is best for all users in all situations. Given this, we believe that to be effective, systems should incorporate a wide variety of such techniques and then some form of overarching framework should be put in place to coordinate them so that only the best recommendations (from whatever source) are presented to the user. To this end, in our previous work, we detailed a market-based approach in which various recommender agents competed with one another to present their recommendations to the user. We showed through theoretical analysis and empirical evaluation with simulated users that an appropriately designed marketplace should be able to provide effective coordination. Building on this, we now report on the development of this multi-agent system and its evaluation with real users. Specifically, we show that our system is capable of consistently giving high quality recommendations, that the best recommendations that could be put forward are actually put forward, and that the combination of recommenders performs better than any constituent recommende

A study of personalisation and the factors affecting the uptake of personal budgets by mental health service users in the UK - A research study commissioned by MIND

This project was commissioned by Mind to add to its knowledge base and existing work on Personalisation so as to support individuals to have greater choice and control over their care and support needs. The project was funded by the Department of Health as part of its Strategic Development fund „Personalisation and Choice of Care and Support (IESD1) 2011‟. This report provides an overview of the main findings of this qualitative study, exploring the concept of personalisation, the factors affecting its operationalisation by voluntary and statutory sector organisations, and service users‟ experiences of its implementation, particularly in relation to what affects their uptake and experience of Personal Budgets. In the course of our investigation into current practice and experience, we have identified a number of barriers and enablers. Our view is that the impact of effective action to tackle the barriers will result in an improved experience of the Personal Budget process and its outcomes for carers and front line staff as well as service users. Recommendations are made for future work in this area

Liquid FM: Recommending Music through Viscous Democracy

Most modern recommendation systems use the approach of collaborative filtering: users that are believed to behave alike are used to produce recommendations. In this work we describe an application (Liquid FM) taking a completely different approach. Liquid FM is a music recommendation system that makes the user responsible for the recommended items. Suggestions are the result of a voting scheme, employing the idea of viscous democracy. Liquid FM can also be thought of as the first testbed for this voting system. In this paper we outline the design and architecture of the application, both from the theoretical and from the implementation viewpoints

When users generate music playlists: When words leave off, music begins?

Music systems that generate playlists are gaining increasing popularity, yet ways to select songs to be acceptable to users is still elusive. We present the results of an explorative study that focused on the language of musically untrained end users for playlist choices, in a variety of listening contexts. Our results indicate that there are a number of opportunities for playlist recommendation or retrieval systems, particularly by taking context into account