TY - GEN
T1 - The blind leading the blind
T2 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases
AU - Malmi, Eric
AU - Solin, Arno
AU - Gionis, Aristides
N1 - VK: Gionis, A.; HIIT
PY - 2015
Y1 - 2015
N2 - We propose a probabilistic method for inferring the geographical locations of linked objects, such as users in a social network. Unlike existing methods, our model does not assume that the exact locations of any subset of the linked objects, like neighbors in a social network, are known. The method efficiently leverages prior knowledge on the locations, resulting in high geolocation accuracies even if none of the locations are initially known. Experiments are conducted for three scenarios: geolocating users of a location-based social network, geotagging historical church records, and geotagging Flickr photos. In each experiment, the proposed method outperforms two state-of-the-art network-based methods. Furthermore, the last experiment shows that the method can be employed not only to network-based but also to content-based location estimation.
AB - We propose a probabilistic method for inferring the geographical locations of linked objects, such as users in a social network. Unlike existing methods, our model does not assume that the exact locations of any subset of the linked objects, like neighbors in a social network, are known. The method efficiently leverages prior knowledge on the locations, resulting in high geolocation accuracies even if none of the locations are initially known. Experiments are conducted for three scenarios: geolocating users of a location-based social network, geotagging historical church records, and geotagging Flickr photos. In each experiment, the proposed method outperforms two state-of-the-art network-based methods. Furthermore, the last experiment shows that the method can be employed not only to network-based but also to content-based location estimation.
UR - http://www.scopus.com/inward/record.url?scp=84959387444&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-23525-7_25
DO - 10.1007/978-3-319-23525-7_25
M3 - Conference contribution
AN - SCOPUS:84959387444
SN - 978-3-319-23524-0
VL - 9285
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 406
EP - 421
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
A2 - Appice, Annalisa
A2 - Rodrigues, Pedro Pereira
A2 - Costa, Vítor Santos
A2 - Gama, João
A2 - Jorge, Alípio
A2 - Soares, Carlos
Y2 - 7 September 2015 through 11 September 2015
ER -