Identifying maps on the World Wide Web

Abstract

This paper presents an automatic approach to mining collections of maps from the Web. Our method harvests images from the Web and then classifies them as maps or non-maps by comparing them to previously classified map and non-map images using methods from Content-Based Image Retrieval (CBIR). Our approach outperforms the accuracy of the previous approach by 20% in F 1-measure. Further, our method is more scalable and less costly than previous approaches that rely on more traditional machine learning techniques. © 2008 Springer-Verlag Berlin Heidelberg.