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 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.

How might a set of term clusters defined by the terms in a document cluster differ from the word clusters found by clustering the terms with K-means?

How could term clustering be used to define clusters of documents?

Cite the sources you use to make your response.