Corpus-Based Analyses of Adjectives:Automatic Clustering
Kuang‐Hua Chen, Hsin‐Hsi Chen · 1994
Similarity analysis is a substantial issue in both corpus-based researches and language usages. This paper focuses on the semantic usages of adjectives, and analyzes the similarities among adjectives. The adjective and the semantic tag of the head noun that it modifies in a noun phrase form a co-occurrence. A two-stage algorithm is applied to clustering the adjectives according to these co-occurrence relationships. Experimental results show that we break even the two issues of large data clustering and meaningful clustering. Paper Category: Topical Paper. Topic Area: Corpus Linguistics, Similarity Analysis, Clustering. 1. Introduction Since the importance of real-world applications is committed in recent years, corpus-based researches become the core of the field of computational linguistics. Many models, such as hidden Markov model, word association model, cache-based model, etc., have been proposed to deal with practical applications. An important problem in these models is how to...