Detalhes bibliográficos
| Resumo: | The pervasiveness of location based services such the GPS on mobile devices enabled the gathering of massive spatial-temporal data. These databases enabled the mining of new data in order to calculate frequent patterns and predict the movement of the objects. In the development of our system for guiding the user with cognitive disabilities (CogHelper) we are applying a trajectory data mining to adapt and adjust the path to user preferences. Indeed, the guiding process may be more useful and it increases the quality of life of the user through this new functionality (conciliated with the speculative computation module). Thus, instead of the user having to adapt to the application we are developing a system that adapts the path to the user. Rather than being guided through the shortest path he may be oriented by a longer but preferred path. The main contribution of this paper is the specification of the trajectory data mining which is incorporated in CogHelper system. |
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| Autores principais: | Ramos, João Ricardo Martins |
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| Outros Autores: | Analide, Cesar; Neves, José; Novais, Paulo |
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| Assunto: | Trajectory Data Mining Frequent Patterns Sequence Mining Clustering |
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| Ano: | 2017 |
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| País: | Portugal |
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| Tipo de documento: | comunicação em conferência |
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| Tipo de acesso: | acesso aberto |
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| Instituição associada: | Universidade do Minho |
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| Idioma: | inglês |
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| Origem: | RepositóriUM - Universidade do Minho |
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