Clustering Word Pairs to Answer Analogy Questions

We focus on answering word analogy questions by using clustering techniques. The increased performance in answering word similarity questions can have many possible applications, including question answering and information retrieval. We present an analysis of clustering algorithms’ performance on answering word similarity questions. This paper’s contributions can be summarized as: (i) casting the problem of solving word analogy questions as an instance of learning clusterings of data and measuring the effectiveness of prominent clustering techniques in learning semantic relations; (ii) devising a heuristic approach to combine the results of different clusterings for the purpose of distinctly separating word pair semantics; (iii) answering SAT-type word similarity questions using our technique.