Maria Teresa Linaza

Bio: Maria Teresa Linaza is an academic researcher. The author has contributed to research in topics: Tourism & Augmented reality. The author has an hindex of 12, co-authored 47 publications receiving 620 citations.

Personalized tourist route generation

Abstract: When tourists are at a destination, they typically search for information in the Local Tourist Organizations There, the staff determines the profile of the tourists and their restrictions Combining this information with their up-to-date knowledge about the local attractions and public transportation, they suggest a personalized route for the tourist agenda Finally, they fine tune up this route to better fit tourists' needs We present an intelligent routing system to fulfil the same task We divide this process in three steps: recommendation, route generation and route customization We focus on the last two steps and analyze them We model the tourist planning problem, integrating public transportation, as the Time Dependent Team Orienteering Problem with Time Windows (TDTOPTW) and we present an heuristic able to solve it on real-time Finally, we show the prototype which generates and customizes routes in real-time

Evaluation of Mobile Augmented Reality Applications for Tourism Destinations

Abstract: Every city contains interesting places and stories to be discovered. Mobile Augmented Reality provides the means to enrich tourists through precise and tailored information about the surroundings of the area they are visiting. MobiAR is an AR platform based on Android, which assists users who need tourist information about a city. When users observe reality through the MobiAR application via their mobile devices, they can experience events that took place at their location through multimedia content, and can access useful information to plan their routes in the city. This paper describes the MobiAR platform and presents the evaluation process that has been applied to the MobiAR application, in order to gather the opinion of real users.

Gamified mobile experiences: smart technologies for tourism destinations

Abstract: The purpose of this paper is twofold: to present gamified mobile experiences as valid tools for DMOs to enrich the experience of tourists, and to present the benefits provided to DMOs by analytics tools integrated on gamified mobile experiences,Staff from three DMOs have generated a gamified mobile experience using a custom authoring tool designed and developed to fulfil their requirements This gamified experience has targeted families with children visiting Basque Country during off-peak season The experience has been validated over a period of seven weeks within a pilot project promoted by the local tourist information offices of the DMOs Data directly provided by tourists and data gathered from analytic tools integrated on the gamified mobile experience have been analysed to fulfil the research objectives presented on the paper,Both DMOs and tourists can benefit from gamified mobile experiences The integration of analytics tools to gain insights into the behaviour of tourists can be a relevant information source for DMOs,The pilot project has targeted a niche tourism market, families with children visiting Basque Country, and has been running during off-peak season Further studies focusing on other tourist types and different tourism season and destination types will be required to strengthen the validation of the research objectives presented on this paper,The paper promotes both the development of gamified mobile experiences and the inclusion of analytics tools for DMOs to obtain relevant information about tourists and the mobile experiences,A gamified mobile experience is generated by DMOs, validated on the basis of experience of real tourists The analytics tools inside the gamified mobile experience provide DMOs with relevant information

Automatic analysis of textual hotel reviews

Abstract: Social Media and consumer-generated content continue to grow and impact the hospitality domain. Consumers write online reviews to indicate their level of satisfaction with a hotel and inform other consumers on the Internet of their hotel stay experience. A number of websites specialized in tourism and hospitality have flourished on the Web (e.g. Tripadvisor). The tremendous growth of these data-generating sources demands new tools to deal with them. To cope with big amounts of customer-generated reviews and comments, Natural Language Processing (NLP) tools have become necessary to automatically process and manage textual customer reviews (e.g. to perform Sentiment Analysis). This work describes OpeNER, a NLP platform applied to the hospitality domain to automatically process customer-generated textual content and obtain valuable information from it. The presented platform consists of a set of Open Source and free NLP tools to analyse text based on a modular architecture to ease its modification and extension. The training and evaluation has been performed using a set of manually annotated hotel reviews gathered from websites like Zoover and HolidayCheck.