Abstract (may include machine translation)
A range of applications, from predicting the spread of human and electronic viruses to city planning and resource management in mobile communications, depend on our ability to understand human activity patterns. I will discuss recent effort to explore human activity patterns, using the mobility of individuals as a proxy. As an application, I will show that by measuring the entropy of each individual’s trajectory, we find can explore the underlying predictability of human mobility, raising fundamental questions on how predictable we really are. I will also discuss the interplay between human mobilty, social links, and the predictive power of data mining.
| Original language | English |
|---|---|
| Title of host publication | Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2011, Proceedings |
| Editors | Dimitrios Gunopulos, Thomas Hofmann, Donato Malerba, Michalis Vazirgiannis |
| Publisher | Springer Verlag |
| Pages | 3 |
| Number of pages | 1 |
| ISBN (Print) | 9783642237799 |
| DOIs | |
| State | Published - 2011 |
| Externally published | Yes |
| Event | European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2011 - Athens, Greece Duration: 5 Sep 2011 → 9 Sep 2011 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 6911 LNAI |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Conference
| Conference | European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2011 |
|---|---|
| Country/Territory | Greece |
| City | Athens |
| Period | 5/09/11 → 9/09/11 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 11 Sustainable Cities and Communities
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