Personalized Intelligent Mobility Platform: An Enrichment Approach Using Social Media

This chapter aims to present a technical approach for developing a personalized mobility knowledge base supported by mechanisms for extracting and processing tweets related with traffic events, in order to support highly specific assistance and recommendations to urban commuters. In order to address a personalized mobility knowledge base, a step-wise approach is presented with the purpose of construction and enriching a knowledge model from heterogeneous data sources providing real-time information via Personal Digital Assistants (PDAs). The approach presented is decomposed into several steps, starting from data collection and knowledge base formalization targeting the development of a personalized intelligent route planner, enabling a more efficient decision support to urban commuters. The work presented here, is still part of ongoing work currently addressed under the EU FP7 MobiS project. Results achieved so far do not address the final conclusions of the project but form the basis for the formalization of the domain knowledge do be acquired.