This article proposes the modified AHC (Agglomerative Hierarchical Clustering) algorithm which considers the feature similarity and is applied to the word clustering. The texts which are given as features for encoding words into numerical vectors are semantic related entities, rather than independent ones, and the synergy effect between the word clustering and the text clustering is expected by combining both of them with each other. In this research, we define the similarity metric between numerical vectors considering the feature similarity, and modify the AHC algorithm byadopting the proposed similarity metric as the approach to the word clustering. The proposed AHC algorithm is empirically validated asthe better approach in clustering words in news articles and opinions. The significance of this research is to improve the clustering performance by utilizing the feature similarities.