Advanced Data Mining Method for Discovering Regions and Trajectories of Moving Objects: “Ciconia Ciconia” Scenario

2008 ◽  
pp. 201-224 ◽  
Author(s):  
Claudio Carneiro ◽  
Arda Alp ◽  
Jose Macedo ◽  
Stefano Spaccapietra
Keyword(s):  
Data Mining ◽  
Moving Objects ◽  
Mining Method ◽  
Ciconia Ciconia ◽  
Data Mining Method

On Predicting the Future Locations of Moving Objects

2016 ◽  
pp. 1899-1917
Author(s):  
Nicola Corona ◽  
Fosca Giannotti ◽  
Anna Monreale ◽  
Roberto Trasarti
Keyword(s):  
Data Mining ◽  
Side Effects ◽  
Mobile Devices ◽  
Moving Objects ◽  
Moving Object ◽  
Location Based Services ◽  
Mining Method ◽  
Data Mining Method ◽  
Mobility Data

The pervasiveness of mobile devices and location-based services produces as side effects an increasing volume of mobility data, which in turn creates the opportunity for a novel generation of analysis methods of movement behaviors. In this chapter, the authors focus on the problem of predicting future locations aimed at predicting with a certain accuracy the next location of a moving object. In particular, they provide a classification of the proposals in the literature addressing that problem. Then the authors preset the data mining method WhereNext and finally discuss possible improvements of that method.

On Predicting the Future Locations of Moving Objects

2014 ◽  
pp. 30-47
Author(s):  
Nicola Corona ◽  
Fosca Giannotti ◽  
Anna Monreale ◽  
Roberto Trasarti
Keyword(s):  
Data Mining ◽  
Side Effects ◽  
Mobile Devices ◽  
Moving Objects ◽  
Moving Object ◽  
Location Based Services ◽  
Mining Method ◽  
Data Mining Method ◽  
Mobility Data

The pervasiveness of mobile devices and location-based services produces as side effects an increasing volume of mobility data, which in turn creates the opportunity for a novel generation of analysis methods of movement behaviors. In this chapter, the authors focus on the problem of predicting future locations aimed at predicting with a certain accuracy the next location of a moving object. In particular, they provide a classification of the proposals in the literature addressing that problem. Then the authors preset the data mining method WhereNext and finally discuss possible improvements of that method.

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