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P-DBSCAN: a density based clustering algorithm for exploration and analysis of attractive areas using collections of geo-tagged photos
P-DBSCAN is presented, a new density-based clustering algorithm based on DBSCAN for analysis of places and events using a collection of geo-tagged photos, and two new concepts are introduced: density threshold, defined according to the number of people in the neighborhood, and adaptive density, which is used for fast convergence towards high density regions. Expand
A conceptual framework and taxonomy of techniques for analyzing movement
A conceptual framework is presented that describes in a systematic and comprehensive way the possible types of information that can be extracted from movement data and on this basis defines the respective types of analytical tasks. Expand
Efficient Multidimensional Suppression for K-Anonymity
In kACTUS, efficient multidimensional suppression is performed, i.e., values are suppressed only on certain records depending on other attribute values, without the need for manually produced domain hierarchy trees. Expand
Spatio-temporal clustering
This chapter focuses on one type of spatio-temporal clustering - trajectory clustering, provides an overview of the state-of-the-art approaches and methods, and presents several scenarios in different application domains such as movement, cellular networks and environmental studies. Expand
Where Would You Go on Your Next Vacation? A Framework for Visual Exploration of Attractive Places
Tourists face a great challenge when they gather information about places they want to visit. Geographically tagged information in the form of Wikipedia pages, local tourist information pages,Expand
Event-Based Analysis of People's Activities and Behavior Using Flickr and Panoramio Geotagged Photo Collections
This paper defines several different tasks related to analysis of attractive places, points of interest and comparison of behavioral patterns of different user communities on geotagged photo data, and provides exploratory visual analysis environment, which allows the analyst to detect spatial and temporal patterns and extract additional knowledge from large geotagging photo collections. Expand
Discovering Landmark Preferences and Movement Patterns from Photo Postings
The approach combines an exploratory spatio-temporal analysis of geographic coordinates and dates representing locations and time of taking photos with basic thematic information available through the Google Maps Web mapping service, and interpretation of the analyzed area. Expand
Analysis of community-contributed space-and time-referenced data (example of Panoramio photos)
This work presents several analysis methods corresponding to two views of space- and time-referenced data published on the Web by general people: as independent spatio-temporal events and as trajectories of people in the geographical space. Expand
Initial Profile Generation in Recommender Systems Using Pairwise Comparison
A comparative field study has been conducted to examine the suitability of the proposed method for eliciting the user's initial profile, and results indicate that the proposed pairwise approach provides more accurate recommendations than existing methods and requires less effort when signing up newcomers. Expand
Analysis of privacy in online social networks of runet
The results indicate that Runet users tend to disclose less information and are more concerned about privacy implications, but there is still a substantial gap between western and Runet SNS providers in understanding of privacy implications and implementation of security measures, which leads to exposure of extensive amounts of personal information. Expand