Discovery of Environmental Web Resources Based on the Combination of Multimedia Evidence

This work proposes a framework for the discovery of environmental Web resources providing air quality measurements and forecasts. Motivated by the frequent occurrence of heatmaps in such Web resources, it exploits multimedia evidence at different stages of the discovery process. Domain-specific queries generated using empirical information and machine learning driven query expansion are submitted both to the Web and Image search services of a general-purpose search engine. Post-retrieval filtering is performed by combining textual and visual (heatmap-related) evidence in a supervised machine learning framework. Our experimental results indicate improvements in the effectiveness when performing heatmap recognition based on SURF and SIFT descriptors using VLAD encoding and when combining multimedia evidence in the discovery process.