Context Relevance Assessment for Recommender systems

Research on context aware recommender systems is taking for granted that context matters. But, often attempts to show the influence of context have failed. In this paper we consider the problem of quantitatively assessing context relevance. For this purpose we are assuming that users can imagine a situation described by a contextual feature, and judge if this feature is relevant for their decision making task. We have designed a UI suited for acquiring such information in a travel planning scenario. In fact, this interface is generic and can also be used for other domains (e.g., music). The experimental results show that it is possible to identify the contextual factors that are relevant for the given task and that the relevancy depends on the type of the place of interest to be included in the plan

Моделювання контексту в рекомендаційних системах

Рекомендаційні системи призначені для формування рекомендацій споживачам відносно вибору товарів та послуг при наявності значної кількості альтернатив. В якості вхідних даних такі системи використовують рейтинги або інформацію про покупки інших користувачів. З використанням машинного навчання формуються залежності між властивостями товарів та характеристиками споживачів.Сфера застосування таких систем пов’язано переважно з використанням e-комерції. Такі системи спрощують вибір користувачам, які не мають достатньо знань про характеристики цікавих для них об’єктів (товарів та послуг) при наявності широкого вибору

Recomendação de pontos de interesse em tempo real com base em contexto

Mestrado em Sistemas de InformaçãoA tecnologia nos dias de hoje assume um papel predominante na vida das pessoas. Um exemplo dominante disto é a internet, um canal de comunicação acessível ao utilizador comum que permite o acesso a uma vasta quantidade de informação. Dada a vastidão da informação acessível aos utilizadores através do uso destes canais de comunicação, torna-se urgente que esses utilizadores consigam extrair de forma rápida e personalizada a informação que pretendem. Para tal existem sistemas de recomendação que permitem combinar várias técnicas computacionais de forma a selecionar itens personalizados de acordo com as características de cada utilizador. Estas características dizem respeito ao perfil, padrões de comportamento, similaridade ou situação contextual dos utilizadores. O objetivo deste trabalho passa pelo desenvolvimento de um sistema de recomendações com base em contexto inserido no domínio do turismo. Pretende-se que um utilizador possa através deste sistema obter recomendações de pontos de interesse turístico elaboradas a partir da consideração de várias condições contextuais que irão ser avaliadas neste trabalho. Pretende-se com a implementação deste sistema realizar um estudo exploratório sobre a relevância do contexto associado às recomendações de forma a perceber como é que este poderá influenciar o resultado de uma recomendação. Irão ser analisadas diversas abordagens tradicionais utilizadas na implementação de sistemas de recomendação e como é que a componente contextual poderá ser adicionada de forma a trazer melhorias substanciais na performance deste tipo de sistema. Irão também ser realizados testes sobre o sistema desenvolvido focados na componente contextual. Estes sistemas permitiram realizar uma análise sobre o contexto considerado a partir da qual será possível identificar que condições contextuais terão uma maior relevância na realização de recomendações, e a partir dela afinar o modelo implementado, através da atribuição de pesos às diferentes condições presentes na componente contextual.The technology nowadays assumes an important role in people's lives. A good example is the internet, a communication channel accessible to ordinary users that allows them the access to vast amounts of information. Given the huge amount of information available to the users it is important that they can extract the information they want in a fast and personalized way. For this purpose there are recommender systems that allow combining several computational techniques in order to select custom items according to characteristics based on each user. These characteristics are related to the profiles, behavior pattern, similarity or contextual situation of the users. This work aims at the development of a contextual recommender system in touristic domain, so that a user can obtain recommendation of points of tourist interest made from the consideration of several contextual conditions that will be evaluated in this work. It is also intended with the implementation of this system to perform an exploratory study about the relevance of the context associated to the recommendations that are made, in order to understand how context can influence the result of a recommendation. There will be an analysis of several recommender systems approaches, and how the contextual component can be added in a way that allows an improvement in the performance of this type of system. Some tests are done focusing in the contextual component. These tests will allow identifying which contextual conditions have more relevance in the results of a recommendation, and tuning the weights assigned to the conditions considered in the system contextual component

A user centred approach to the modelling of contextualised experience adaptation in relation to video consumption

This research focused on the development of a user centric framework for the interpretation of contextualised TV and video viewing experiences (UX). Methods to address content overload and provide better contextualisation when consuming video have been an area of academic discussion for almost 20 years (Burke, Felfernig, & Goker, 2011). However over the same period technical system design for video has actually moved away from attempts to model the nature of real viewing contexts. With now near ubiquitous access to video from a range of disparate devices the addition of contextualisation within video applications and devices represents an opportunity in terms of improving viewer UX. Three user studies were carried out to inform development of the framework and employed mixed method approaches. The first focused on understanding where video is watched and the contextual factors that defined those places as viewing situations. This study derived eight Archetype viewing situations and associated contextual cues. The second study measured viewing UX in context. Significant differences in subjective ratings for measured UX were found when viewing was compared within subjects across Viewing Archetype situations. A third study characterised viewing UX, identifying behavioural, environmental and technological factors which through observed frequency and duration were identified as indicative enablers and detractors in the creation of viewing UX. Concepts generated within the studies that related to viewing context identification and viewing UX classification through experiential factors were integrated into the framework. The framework provides a way through which to identify, describe and improve viewing UX across contexts. Additionally the framework was referenced to develop an exemplar system model for contextual adaptation in order to show its relevance to the generation of technical system design. Finally information for designers was created in the form of scenarios and suggestions for use in order to bring the framework to life as a resource for development teams