Word Clustering

This chapter is concerned with the process of clustering words semantically. In the previous chapter, we studied the process of classifying a word into a category as an instance of word mining. In word clustering, which we study in this chapter, words are encoded into numerical vectors whose features are texts, and similarity metrics such as cosine similarity and Euclidean distance are defined as essential operations for word clustering. Although lexical word clustering, which is the process of clustering words based on their spellings, exists, it will be excluded in the scope of this chapter. This chapter is intended to describe the process of clustering words semantically as another instance of word mining.