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This book is concerned with table-based machine learning algorithms which are applied to word clustering. The book is authored by collecting slides about the application of machine learning algorithms to word clustering; each page is given as a slide. This book is intended for ones who study applications of machine learning algorithms to word clustering and is composed of five sections. Word clustering is defined as the process of segmenting a word group into subgroups each of which contains semantically similar words; in this book, the scope is restricted to only semantic word clustering. This book covers table based modified versions of AHC Algorithm, K means algorithm, Linear Online Clustering Algorithm, and Divisive Algorithm, as approaches to word clustering.
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