Aggregating social media data with temporal and environmental context for recommendation in a mobile tour guide system

Abstract

Purpose-Increasingly manufacturers of smartphone devices are utilising a diverse range of sensors. This innovation has enabled developers to accurately determine a user's current context. One area that has been significantly enhanced by the increased use of context in mobile applications is tourism. Traditionally tour guide applications rely heavily on location and essentially ignore other types of context. This has led to problems of inappropriate suggestions and tourists experiencing information overload. These problems can be mitigated if appropriate personalisation and content filtering is performed. This research proposes an intelligent context aware recommender system that aims to minimise the highlighted problems. Design / Methodology / Approach-Intelligent reasoning was performed to determine the weight or importance of each different type of environmental and temporal context. Environmental context such as the weather outside can have an impact on the suitability of tourist attractions. Temporal context can be the time of day or season; this is particularly important in tourism as it is largely a seasonal activity. Social context such as social media can potentially provide an indication of the 'mood' of an attraction. These types of context are combined with location data and the context of the user to provide a more effective recommendation to tourists. The evaluation of the system is a user study that utilised both qualitative and quantitative methods, involving forty participants of differing gender, age group, number of children and marital status. Findings-This study revealed that the participants selected the context based recommendation at a significantly higher level than either location based recommendation or random recommendation. It was clear from analysing the questionnaire results that location is not the only influencing factor when deciding on a tourist attraction to visit. Research Limitations / Implications-In order to effectively determine the success of the recommender system, various combinations of contextual conditions were simulated. Simulating contexts provided the ability to randomly assign different contextual conditions to ensure an effective recommendation under all circumstances. This is not a reflection of the 'real world' because in a 'real world' field study the majority of the contextual conditions will be similar. For example, if a tourist visited numerous attractions in one day, then it is likely that the weather conditions would be the same for the majority of the day, especially in the summer season. Practical Implications-Utilising this type of recommender system would allow the tourists to "go their own way" rather than following a prescribed route. By using this system, tourists can co-create their own experience using both social media and mobile technology. This increases the need to retain user preferences and have it available for multiple destinations. The application will be able to learn further through multiple trips and as a result the personalisation as...

Progress on technology use in tourism

“…Some studies indicate the importance of using technologies in a strategic manner especially in terms of social media and online presence. (Reino et al, 2016), the vast number of applications that near field communication technologies have for the tourism industry (Egger, 2013), the use of intelligent context-aware recommender system that takes into account temporal and social context in tour guide applications (Meehan et al, 2016) or the strategic use of Customer Relationship Management systems in tourism as a whole (Vogt, 2011, Mohammed et al, 2017.…”

“…Content requirement, functional requirement, comfort, experience and resistance are significant user requirement for developing the wearable AR museum application(tom Dieck et al, 2016). Given the heavy reliance of location-based recommendation in tour guide application,Meehan et al (2016)'s study found that environmental, temporal and social these three contextual conditions at a significantly higher level of influence in mobile recommender systems.In terms of research into ICT from a perspective of user support, studies investigated the supportive role of interactive mobile technologies in hotel guests' facilitation of transactions. The adoption of these technologies can mediate the experiences of guests in hotel service settings, with importance placed on cognitive absorption, playfulness, and security (WendyZhu and Morosan, 2014).…”

Cocriação de Valor no Turismo

“…O papel das tecnologias, especialmente as de comunicação, evidencia a cada dia a relação entre a cocriação de valor e a intenção de recomendação boca-a-boca (WoM). O uso das tecnologias parece aumentar a cocriação de valor no turismo de pelo menos duas maneiras: primeiro, elas permitem a personalização de produtos turísticos e suas experiências (Hsu, King, & Buhalis, 2016;Meehan, Lunney, Curran, & McCaughey, 2016;Sarmah, Rahman, & Kamboj, 2017); segundo, seu uso amplia o alcance das interações sociais, permitindo que turistas e outras partes interessadas compartilhem suas opiniões (positivas ou negativas) em diferentes plataformas (Novak & Schwabe, 2009;Cabiddu, Lui, & Piccoli, 2013). Isto significa dizer que a cocriação de valor e o compartilhamento dessas experiências são estimuladas.…”

The role of social media in shaping airline’s image

“…This can often be problematic in a fast-paced industry, which can also be prone to delays and last-minute changes. According to Meehan et al, (2016), social media gives people the opportunity to provide feedback and share thoughts regarding their travel experiences. Customer experience is everything in the airline industry.…”