title: Collective Prediction of Individual Mobility Traces for Users with Short Data History.
abstract: We present and test a sequential learning algorithm for the prediction of human mobility that leverages large datasets of sequences to improve prediction accuracy, in particular for users with a short and non-repetitive data history such as tourists in a foreign country. The algorithm compensates for the difficulty of predicting the next location when there is limited evidence of past behavior by leveraging the availability of sequences of other users in the same system that provide redundant records of typical behavioral patterns. We test the method on a dataset of 10 million roaming mobile phone users in a European country. The average prediction accuracy is significantly higher than that of individual sequence prediction algorithms, primarily constant order Markov models derived from the user's own data, that have been shown to achieve high accuracy in previous studies of human mobility. The proposed algorithm is generally applicable to improve any sequential prediction when there is a sufficiently rich and diverse dataset of sequences.
authors.affiliation: Department of Geoinformatics - Z_GIS, University of Salzburg, Salzburg, Austria.|CS Research Foundation, Amsterdam, The Netherlands.
authors.forename: Bartosz
authors.identifier: http://orcid.org/0000-0003-0566-2655
authors.initials: B
authors.lastname: Hawelka
authors.affiliation: Department of Geoinformatics - Z_GIS, University of Salzburg, Salzburg, Austria.|CS Research Foundation, Amsterdam, The Netherlands.
authors.forename: Izabela
authors.initials: I
authors.lastname: Sitko
authors.affiliation: CS Research Foundation, Amsterdam, The Netherlands.
authors.forename: Pavlos
authors.initials: P
authors.lastname: Kazakopoulos
authors.affiliation: Department of Geoinformatics - Z_GIS, University of Salzburg, Salzburg, Austria.|CS Research Foundation, Amsterdam, The Netherlands.
authors.forename: Euro
authors.initials: E
authors.lastname: Beinat
mesh_terms: D000465:Algorithms; D040421:Cell Phone; D019992:Databases as Topic; D063426:Human Migration; D006801:Humans