Clusters of documents can be summarized by finding the top terms (words) for the documents in the

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Clusters of documents can be summarized by finding the top terms (words) for the documents in the cluster, e.g., by taking the most frequent k terms, where k is a constant, say 10, or by taking all terms that occur more frequently than a specified threshold. Suppose that K-means is used to find clusters of both documents and words for a document data set
(a) How might a set of term clusters defined by the top terms in a document cluster differ from the word clusters found by clustering the terms with K-means?
(b) How could term clustering be used to define clusters of documents?
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Introduction to Data Mining

ISBN: 978-0321321367

1st edition

Authors: Pang Ning Tan, Michael Steinbach, Vipin Kumar

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