COFE: A Scalable Method for Feature Extraction from Complex Objects

Abstract. Feature Extraction, also known as Multidimensional Scaling, is a basic primitive associated with indexing, clustering, nearest neighbor searching and visualization. We consider the problem of feature extraction when the data-points are complex and the distance evaluation function is very expensive to evaluate. Examples of expensive distance evaluations include those for computing the Hausdorff distance between polygons in a spatial database, or the edit distance between macromolecules in a DNA or protein database. While feature extraction is a well-studied problem in the databases and statistics communities, almost all methods known require that the distance between every pair of points be evaluated. This is prohibitive, even for small databases, when the distance function is expensive. We propose Cofe, a method for sparse feature extraction which is based on novel random non-linear projections. We evaluate Cofe on real data and find that it performs very well in terms of q...

• Type: Conference
• Year: 2000
• Where: DAWAK
• Authors: Gabriela Hristescu, Martin Farach-Colton
• Keywords: DAWAK 2000, Distance Evaluations, Expensive Distance Evaluations, Feature Extraction, Information Management