Clustering plays an integral role in data-mining computations. Clustering groups together similar items of a dataset using one or more features of the data items based on the use case. Document clustering is used in many text-mining operations such as document organization, topic identification, information presentation, and so on. Document clustering shares many of the mechanisms and algorithms with traditional data clustering mechanisms. However, document clustering has its unique challenges when it comes to determining the features to use for clustering and when building vector space models to represent the text documents.

The Running K-means with Mahout recipe of Chapter 7, Hadoop Ecosystem II – Pig, HBase, Mahout, and Sqoop focuses on using Mahout KMeansClustering to cluster a statistics data. The Clustering an Amazon sales dataset recipe of Chapter 8, Classifications, Recommendations, and Finding Relationships of the previous edition of this...