Independent component analysis: algorithms and applications
Neural Networks
Towards extracting flickr tag semantics
Proceedings of the 16th international conference on World Wide Web
Towards automatic extraction of event and place semantics from flickr tags
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Generating diverse and representative image search results for landmarks
Proceedings of the 17th international conference on World Wide Web
Methods for extracting place semantics from Flickr tags
ACM Transactions on the Web (TWEB)
Event detection from flickr data through wavelet-based spatial analysis
Proceedings of the 18th ACM conference on Information and knowledge management
The wisdom of social multimedia: using flickr for prediction and forecast
Proceedings of the international conference on Multimedia
Research and applications on georeferenced multimedia: a survey
Multimedia Tools and Applications
Geotagging in multimedia and computer vision--a survey
Multimedia Tools and Applications
Geographical topic discovery and comparison
Proceedings of the 20th international conference on World wide web
Exploration and comparison of geographic information sources using distance statistics
Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Proceedings of the fifth ACM international conference on Web search and data mining
Learning landmarks by exploiting social media
MMM'10 Proceedings of the 16th international conference on Advances in Multimedia Modeling
Mining photo-sharing websites to study ecological phenomena
Proceedings of the 21st international conference on World Wide Web
Discovering geographical topics in the twitter stream
Proceedings of the 21st international conference on World Wide Web
Face recognition by independent component analysis
IEEE Transactions on Neural Networks
Methods for extracting place semantics from Flickr tags
ACM Transactions on the Web (TWEB)
A probablistic model for spatio-temporal signal extraction from social media
Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Spatio-temporal characteristics of bursty words in Twitter streams
Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Reliable spatio-temporal signal extraction and exploration from human activity records
SSTD'13 Proceedings of the 13th international conference on Advances in Spatial and Temporal Databases
A method of Area of Interest and Shooting Spot Detection using Geo-tagged Photographs
Proceedings of The First ACM SIGSPATIAL International Workshop on Computational Models of Place
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In this work we present a framework for the unsupervised extraction of latent geographic features from georeferenced social media. A geographic feature represents a semantic dimension of a location and can be seen as a sensor that measures a signal of geographic semantics. Our goal is to extract a small number of informative geographic features from social media, to describe and explore geographic space, and for subsequent spatial analysis, e.g., in market research. We propose a framework that, first, transforms the unstructured and noisy geographic information in social media into a high-dimensional multivariate signal of geographic semantics. Then, we use dimensionality reduction to extract latent geographic features. We conduct experiments using two large-scale Flickr data sets covering the LA area and the US. We show that dimensionality reduction techniques extracting sparse latent features find dimensions with higher informational value. In addition, we show that prior normalization can be used as a parameter in the exploration process to extract features representing different geographic characteristics, that is, landmarks, regional phenomena, or global phenomena.