The problem of graph classification has attracted great interest in the last decade. Current research on graph classification assumes the existence of large amounts of labeled tra...
Abstract. We present a hybrid machine learning approach for information extraction from unstructured documents by integrating a learned classifier based on the Maximum Entropy Mod...
As XML is gathering more and more importance in the field of data interchange in distributed business to business (B2B) applications, it is increasingly important to provide a for...
Centroid Classifier has been shown to be a simple and yet effective method for text categorization. However, it is often plagued with model misfit (or inductive bias) incurred by i...
Abstract. Many SQL queries with aggregated subqueries exhibit redundancy (overlap in FROM and WHERE clauses). We propose a method, called the for-loop, to optimize such queries by ...