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Poi engine - Sistema automático de pesquisa e recolha de pontos de interesses turísticos relativos a formação na área da saúde
| Name: | Description: | Size: | Format: | |
|---|---|---|---|---|
| 5.25 MB | Adobe PDF |
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Abstract(s)
Sendo o turismo um dos grandes fatores económicos e sociais de alguns países, e também uma percentagem de 2.9% do PIB mundial, faz com que a área de planeamento de rotas turísticas, de grande importância (Silva 2014).
Muitos desses turistas, planeiam as suas viagens através da internet escolhendo os pontos turísticos que pretendem visitar. Esta atividade torna-se stressante devido à quantidade excessiva de informação que se obtém ao pesquisar por informação turística em motores de pesquisa convencionais (Ciurana Simó 2012). Uma forma de minimizar este esforço é utilizar sistemas de recomendação que permitem filtrar a informação, minimizando a quantidade de informação irrelevante (Ciurana Simó 2012).
Surgem com regularidade novos interesses e categorias de turismo, como, o turismo desportivo e o turismo medicinal (Mun et al. 2015). Uma categoria de turismo em crescimento neste momento é o turismo profissional, sendo que este, normalmente, é de curto prazo. Os sistemas de recomendação, em geral, recomendam nesta categoria, sugestões de restauração, transportes e museus, o que torna a categoria demasiado generalista.
O objetivo do presente projeto tem como foco uma subcategoria de turismo profissional, o turismo para profissionais de saúde. Os profissionais de saúde necessitam de se manter informados e formados nas melhores práticas e opções disponíveis para o tratamento de doenças e lesões dos seus pacientes. Para isso, começam a não ter o tempo disponível para assistir a eventos formativos dentro da área profissional em que trabalham (Smith et al. 2009).
Muitos desses eventos decorrem em localizações turísticas, sendo aqui que este projeto contribui.
Neste projeto, foi criado um protótipo que recolhe a informação existente sobre estes eventos formativos, através de pesquisas avançadas. Disponibiliza essa informação a sistemas de recomendação turísticos sob a forma de ponto de interesse. Com esta informação acessível, os profissionais de saúde podem assim a planear as suas rotas turísticas nas suas férias de uma forma mais agradável.
Being tourism a major economic and social factor in some countries, with a percentage of 2.9% of world GDP, makes planning tourism routes of great importance (Silva 2014). Many of these tourists use the Internet to plan their trips and to pick points of interest to visit, this quickly becomes a stressful activity due to the excessive amount of information obtained while searching for touristic information on conventional search engines (Ciurana Simó 2012). A way to minimize this effort is by using recommendation systems applications, which filter information minimizing the amount of unwanted data (Ciurana Simó 2012). There are new interests and tourism categories emerging like sports tourism and the medicinal tourism (Mun et al. 2015). A tourism category emerging is the professional tourism, and is usually short-term tourism. In general, recommendation systems, recommend for this category, suggestions in food industry, transportation, museums, treating this category as a general one. The objective of this thesis is focused on a subcategory of professional tourism, tourism for health care professionals. These professionals need to be up to date with late knowledge and practices to better treat their patients. To do so, they must attend to lectures and professionals practice courses, which most times they don’t have the time available to attend (Smith et al. 2009). Many events in the health care area emerge in tourism locations, this is where the topic of this thesis is centered and where it contributes. In this project, an application prototype was developed to collect existing information on these academic events. Providing it to recommendation systems has point of interest, this will help the health care professionals to plan their tourism routes in a more pleasing way.
Being tourism a major economic and social factor in some countries, with a percentage of 2.9% of world GDP, makes planning tourism routes of great importance (Silva 2014). Many of these tourists use the Internet to plan their trips and to pick points of interest to visit, this quickly becomes a stressful activity due to the excessive amount of information obtained while searching for touristic information on conventional search engines (Ciurana Simó 2012). A way to minimize this effort is by using recommendation systems applications, which filter information minimizing the amount of unwanted data (Ciurana Simó 2012). There are new interests and tourism categories emerging like sports tourism and the medicinal tourism (Mun et al. 2015). A tourism category emerging is the professional tourism, and is usually short-term tourism. In general, recommendation systems, recommend for this category, suggestions in food industry, transportation, museums, treating this category as a general one. The objective of this thesis is focused on a subcategory of professional tourism, tourism for health care professionals. These professionals need to be up to date with late knowledge and practices to better treat their patients. To do so, they must attend to lectures and professionals practice courses, which most times they don’t have the time available to attend (Smith et al. 2009). Many events in the health care area emerge in tourism locations, this is where the topic of this thesis is centered and where it contributes. In this project, an application prototype was developed to collect existing information on these academic events. Providing it to recommendation systems has point of interest, this will help the health care professionals to plan their tourism routes in a more pleasing way.
Description
Keywords
Sistemas de recomendação Turismo Turismo profissional Pontos de interesse Recommendation system Tourism Professional tourism Points of interest