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Istituto di Scienza e Tecnologie dell'Informazione     
Paes Leme L. A., Renso C., Pereira Nunes B., Rabelo Lopez G., Casanova M. A., Ponte Vidal V. Searching for data sources for the semantic enrichment of trajectories. In: WISE 2016 - Web Information Systems Engineering. 17th International Conference (Shangai, China, 8-10 November 2016). Proceedings, vol. II pp. 238 - 246. Wojciech Cellary, Mohamed F. Mokbel, Jianmin Wang, Hua Wang, Rui Zhou, Yanchun Zhang. (Lecture Notes in Computer Science, vol. 10042). Springer, 2016.
 
 
Abstract
(English)
The fast growing number of datasets available on the Web inspired researchers to propose innovative techniques to combine spatio-temporal data with contextual data. However, as the number of datasets has increased relatively fast, finding the most appropriate datasets for enrichment also became extremely difficult. This paper proposes an innovative approach to rank a set of datasets according to the likelihood that they contain relevant enrichments. The approach is based on the intuition that the sequence of places visited during a trajectory can induce the best datasets to enrich the trajectory. It relies on a supervised approach to learn rules of association between visited places and meaningful datasets.
URL: http://link.springer.com/chapter/10.1007/978-3-319-48743-4_19
DOI: 10.1007/978-3-319-48743-4_19
Subject Trajectory Semantic enrichment,
Linked Open data
H.2.8 DATABASE MANAGEMENT. Database Applications
68W99 Computer science


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