Beyond co-occurrence: discovering and visualizing tag relationships from geo-spatial and temporal similarities

Studying relationships between keyword tags on social sharing websites has become a popular topic of research, both to improve tag suggestion systems and to discover connections between the concepts that the tags represent. Existing approaches have largely relied on tag co-occurrences. In this paper, we show how to find connections between tags by comparing their distributions over time and space, discovering tags with similar geographic and temporal patterns of use. Geo-spatial, temporal and geo-temporal distributions of tags are extracted and represented as vectors which can then be compared and clustered. Using a dataset of tens of millions of geo-tagged Flickr photos, we show that we can cluster Flickr photo tags based on their geographic and temporal patterns, and we evaluate the results both qualitatively and quantitatively using a panel of human judges. We also develop visualizations of temporal and geographic tag distributions, and show that they help humans recognize semanti...

• Type: Journal
• Year: 2012
• Where: WSDM
• Authors: Haipeng Zhang, Mohammed Korayem, Erkang You, David J. Crandall
• Keywords: Data Mining, Flickr Photo Tags, Suggestion Systems, Temporal Distributions, WSDM 2012