Kernel methods in general and support vector machines in particular have been successful
in various learning tasks on data represented in a single table. Much'real-world'data …

Abstract Inductive Logic Programming (ILP) is an area of Machine Learning which has now
reached its twentieth year. Using the analogy of a human biography this paper recalls the …

In this paper we present 1BC and 1BC2, two systems that perform naive Bayesian
classification of structured individuals. The approach of 1BC is to project the individuals …

Propositionalization has already been shown to be a promising approach for robustly and
effectively handling relational data sets for knowledge discovery. In this paper, we compare …

Proteins are the most essential and versatile macromolecules of life, and the knowledge of
their functions is a crucial link in the development of new drugs, better crops, and even the …

This book provides a unique treatment of an important area of machine learning and
answers the question of how kernel methods can be applied to structured data. Kernel …

Identifier attributes—very high-dimensional categorical attributes such as particular product
ids or people's names—rarely are incorporated in statistical modeling. However, they can …

KDD Cup 2001 Report Page 1 KDD Cup 2001 Report Jie Cheng Canadian Imperial Bank of
Commerce Global Analytics Jie.cheng@cibc.ca Mark-A. Krogel School of Computer Science …

One basic goal in the analysis of time-series data is to find frequent interesting episodes, ie,
collections of events occurring frequently together in the input sequence. Most widely-known …

Relational data representations have become an increasingly important topic due to the
recent proliferation of network datasets (eg, social, biological, information networks) and a …