(2009) describe a further empirical analysis of the seed construction and its influence on the learning performance and show that size, arity and distinctiveness of the seed examples play various important roles for the learning performance.
the system demonstrated here, called META-DARE, serves as a monitoring and analysis system for conducting various experiments with seed-based minimally supervised machine learning.