Corpus-based semantic class mining: Distributional vs. pattern-based approaches

Abstract

Main approaches to corpus-based semantic class mining include distributional similarity (DS) and pattern-based (PB). In this paper, we perform an empirical comparison of them, based on a publicly available dataset containing 500 million web pages, using various categories of queries. We further propose a frequency based rule to select appropriate approaches for different types of terms.