Community-Based Geospatial Tag Estimation
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© 2016 IEEE. This paper tackles the geospatial tag estimation problem, which is of critical importance for location-based search, retrieval, and mining applications. However, tag estimation is challenging due to massive sparsity, uncertainty in the tags actually used, as well as diversity across locations and times. Toward overcoming these challenges, we propose a community-based smoothing approach that seeks to uncover hidden conceptual communities which link multiple related locations by their common interests in addition to their proximity. Through extensive experiments over a sample of millions of geotagged Twitter posts, we demonstrate the effectiveness of the smoothing approach and validate the intuition that geo-locations have the tendency to share similar 'ideas' in the formation of conceptual communities.
author list (cited authors)
Niu, W., Caverlee, J., Lu, H., & Kamath, K.
editor list (cited editors)
Kumar, R., Caverlee, J., & Tong, H.