TY - GEN
T1 - A novel approach to mining travel sequences using collections of geotagged photos
AU - Kisilevich, Slava
AU - Keim, Daniel
AU - Rokach, Lior
PY - 2010/1/1
Y1 - 2010/1/1
N2 - In this paper we present a novel approach for analyzing the trajectories of moving objects and of people in particular. The mined data from these sequences can provide valuable information for understanding the surrounding locations, discovering attractive place or mining frequent sequences of visited places. Based on geotagged photos, our framework mines semantically annotated sequences. Our framework is capable of mining semantically annotated sequences of any length to discover patterns that are not necessarily immediate antecedents. The approach consists of four main steps. In the first step, every photo location is semantically annotated by assigning it to a known nearby point of interest. In the second step, a density-based clustering algorithm is applied to all unassigned photos, creating regions of unknown points of interest. In the third step, a travel sequence of every individual is built. In the final step, travel sequence patterns are mined using the semantics that were obtained from the first two steps. Case studies of Guimarães, Portugal (where the conference takes place) and Berlin, Germany demonstrate the capabilities of the proposed framework.
AB - In this paper we present a novel approach for analyzing the trajectories of moving objects and of people in particular. The mined data from these sequences can provide valuable information for understanding the surrounding locations, discovering attractive place or mining frequent sequences of visited places. Based on geotagged photos, our framework mines semantically annotated sequences. Our framework is capable of mining semantically annotated sequences of any length to discover patterns that are not necessarily immediate antecedents. The approach consists of four main steps. In the first step, every photo location is semantically annotated by assigning it to a known nearby point of interest. In the second step, a density-based clustering algorithm is applied to all unassigned photos, creating regions of unknown points of interest. In the third step, a travel sequence of every individual is built. In the final step, travel sequence patterns are mined using the semantics that were obtained from the first two steps. Case studies of Guimarães, Portugal (where the conference takes place) and Berlin, Germany demonstrate the capabilities of the proposed framework.
KW - Sequence mining
KW - Sequence patterns
KW - Trajectories
UR - http://www.scopus.com/inward/record.url?scp=84883065429&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-12326-9_9
DO - 10.1007/978-3-642-12326-9_9
M3 - Conference contribution
AN - SCOPUS:84883065429
SN - 9783642123252
T3 - Lecture Notes in Geoinformation and Cartography
SP - 163
EP - 182
BT - Geospatial Thinking
PB - Kluwer Academic Publishers
T2 - 13th AGILE International Conference on Geographic Information Science, AGILE 2010
Y2 - 10 May 2010 through 14 May 2010
ER -