Unsupervised learning by probabilistic latent semantic analysis
Machine Learning
The Journal of Machine Learning Research
The Story Picturing Engine---a system for automatic text illustration
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Generating diverse and representative image search results for landmarks
Proceedings of the 17th international conference on World Wide Web
Learning to reduce the semantic gap in web image retrieval and annotation
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Methods for extracting place semantics from Flickr tags
ACM Transactions on the Web (TWEB)
Generating location overviews with images and tags by mining user-generated travelogues
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Methods for extracting place semantics from Flickr tags
ACM Transactions on the Web (TWEB)
Learning to associate relevant photos to georeferenced textual documents
Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Geo-Location estimation of flickr images: social web based enrichment
ECIR'12 Proceedings of the 34th European conference on Advances in Information Retrieval
Placing images on the world map: a microblog-based enrichment approach
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
A study on the accuracy of Flickr's geotag data
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Enhancing news organization for convenient retrieval and browsing
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
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A travelogue can be regarded as a location-oriented or scene-based document. Visualizing a pure textual travelogue with location-based images makes it convenient for readers to understand the main content of the travelogue and thus share the author's experience. Though a large number of images exist in web albums such as Flickr, they are not directly, explicitly associated with a travelogue. In this paper, we propose a general framework and four approaches to accomplish the visualization task. The first step of the framework is to extract location names and other location-related information from a travelogue (or a set of travelogues). In the second step, we use the location names as queries to retrieve candidate images together with their tags from Flickr. In the last step, the retrieved images are carefully refined by using a proper similarity function. The similarity function measures the similarity between the travelogue and the tags of each candidate Flickr image. In addition to the framework, our main contributions lie in three topic models which are used for computing the similarity functions. The models are not only adopted to visualize a single travelogue but also employed to summarize a collection of travelogues. Experimental results on a set of Chinese travelogues demonstrate the proposed methods' ability to visualize travelogues.