• Publications
  • Influence
Visually driven analysis of movement data by progressive clustering
TLDR
The paper investigates the possibilities of using clustering techniques in visual exploration and analysis of large numbers of trajectories, that is, sequences of time-stamped locations of some moving entities, where a simple distance function with a clear meaning is applied on each step leads to easily interpretable outcomes. Expand
Returners and explorers dichotomy in human mobility
TLDR
We show that returners and explorers play a distinct quantifiable role in spreading phenomena and that a correlation exists between their mobility and social interactions. Expand
Interactive visual clustering of large collections of trajectories
TLDR
We propose an approach to extracting meaningful clusters from large databases by combining clustering and classification, which are driven by a human analyst through an interactive visual interface. Expand
Unveiling the complexity of human mobility by querying and mining massive trajectory data
TLDR
We present the results of a large-scale experiment, based on the detailed trajectories of tens of thousands private cars with on-board GPS receivers, tracked during weeks of ordinary mobile activity. Expand
Movement data anonymity through generalization
TLDR
In recent years, spatio-temporal and moving objects databases have gained considerable interest, due to the diffusion of mobile devices (e.g., mobile phones, RFID devices and GPS devices) and new applications, where the discovery of consumable, concise, and applicable knowledge is the key step. Expand
From movement tracks through events to places: Extracting and characterizing significant places from mobility data
TLDR
We propose a visual analytics procedure for analyzing movement data, i.e., recorded tracks of moving objects. Expand
Spatio-temporal clustering
TLDR
Spatio-temporal clustering is a process of grouping objects based on their spatial and temporal similarity. Expand
Scalable Analysis of Movement Data for Extracting and Exploring Significant Places
TLDR
We propose a visual analytics procedure for place-oriented analysis of movement data that includes (1) visually-supported extraction of relevant m-events based on event clustering; 3) spatiotemporal aggregation of events or trajectories; 4) analysis of the aggregated data. Expand
Identifying users profiles from mobile calls habits
TLDR
We propose a methodology to partition the users tracked by GSM phone calls into profiles like resident, commuters, in transit and tourists. Expand
A Novel Approach to Evaluate Community Detection Algorithms on Ground Truth
TLDR
We propose a novel approach aimed at evaluating the adherence of a community partition to the ground truth: our methodology provides more information than the state-of-the-art and is fast to compute on large-scale networks. Expand
...
1
2
3
4
5
...