Paper: Representing Topics Using Images

ACL ID N13-1016
Title Representing Topics Using Images
Venue Annual Conference of the North American Chapter of the Association for Computational Linguistics
Session Main Conference
Year 2013
Authors

Topics generated automatically, e.g. using LDA, are now widely used in Computational Linguistics. Topics are normally represented as a set of keywords, often the n terms in a topic with the highest marginal probabilities. We introduce an alternative approach in which topics are represented using images. Candi- date images for each topic are retrieved from the web by querying a search engine using the top n terms. The most suitable image is se- lected from this set using a graph-based al- gorithm which makes use of textual informa- tion from the metadata associated with each image and features extracted from the images themselves. We show that the proposed ap- proach significantly outperforms several base- lines and can provide images that are useful to represent a topic.