Adapting the user path through trajectory data mining

• Main Author: Ramos, João Ricardo Martins
• Publication Date: 2017
• Other Authors: Analide, Cesar, Neves, José, Novais, Paulo
• Language: eng
• Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
• Download full: http://hdl.handle.net/1822/50519
• topic: Trajectory Data Mining; Frequent Patterns; Sequence Mining; Clustering; Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática; Science & Technology

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.