Artificial Intelligence

    

Clustering Words Semantically by Graph based Version of AHC Algorithm

Authors: Taeho Jo

This article proposes the modified AHC (Agglomerative Hierarchical Clustering) algorithm which clusters graphs, instead of numerical vectors, as the approach to the word clustering. The graph is more graphical for representing a word and the synergy effect between the text clustering and the word clustering is expected by combining them with each other. In this research, we propose the similarity metric between two graphs representing words, and modify the AHCalgorithm by adopting the proposed similarity metric as the approach to the word clustering. The proposed AHC algorithm is empiricallyvalidated as the better approach in clustering words in news articles and opinions. In this article, a word is encoded into a weighted and undirected graph and it is represented into a list of edges.

Comments: 11 Pages.

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Submission history

[v1] 2024-05-29 02:56:04

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