Collaborative recommendations with content-based filters for cultural activities via a scalable event distribution platform

Nowadays, most people have limited leisure time and the offer of (cultural) activities to spend this time is enormous. Consequently, picking the most appropriate events becomes increasingly difficult for end-users. This complexity of choice reinforces the necessity of filtering systems that assist users in finding and selecting relevant events. Whereas traditional filtering tools enable e.g. the use of keyword-based or filtered searches, innovative recommender systems draw on user ratings, preferences, and metadata describing the events. Existing collaborative recommendation techniques, developed for suggesting web-shop products or audio-visual content, have difficulties with sparse rating data and can not cope at all with event-specific restrictions like availability, time, and location. Moreover, aggregating, enriching, and distributing these events are additional requisites for an optimal communication channel. In this paper, we propose a highly-scalable event recommendation platform which considers event-specific characteristics. Personal suggestions are generated by an advanced collaborative filtering algorithm, which is more robust on sparse data by extending user profiles with presumable future consumptions. The events, which are described using an RDF/OWL representation of the EventsML-G2 standard, are categorized and enriched via smart indexing and open linked data sets. This metadata model enables additional content-based filters, which consider event-specific characteristics, on the recommendation list. The integration of these different functionalities is realized by a scalable and extendable bus architecture. Finally, focus group conversations were organized with external experts, cultural mediators, and potential end-users to evaluate the event distribution platform and investigate the possible added value of recommendations for cultural participation

Film and Tourism. An Information System for Disclosing the Cinematographic Attractiveness of Destinations (Giulia Lavarone pp.289-291)

The Department of Cultural Heritage of the University of Padova investigated the topic of film-induced tourism in a year-long project, concluded in April 2015, titled Strumenti innovativi per la promozione turistica: film-induced tourism (Novel Tools to Promote Tourism: Film-induced Tourism). The project was financed by the Veneto Region through ESF funds. It brought together the expertise of film scholars, computer scientists and destination management experts, in partnership with public bodies (Provincia di Padova) and ICT companies. The goal of the project was to develop an information system that fosters film-induced tourism combining data about a geographical area and the movies produced in it. The system is designed as a platform to store and convey rich contents, able to address the needs of the tourist but also of stakeholders as DMOs and film commissions. The system was planned as a model for the destinations which could take advantage of a significant cinematographic background, yet are unlikely to spontaneously produce considerable film-induced tourism phenomena. The province of Padova has been used as a case study

Early evaluation of Unistats: user experiences

This paper sets out the findings of the user evaluation of Unistats.UK Higher Education Funding Bodie