Toward Parallel Document Clustering

A key challenge to automated clustering of documents in large text corpora is the high cost of comparing documents in a multi-million dimensional document space. The Anchors Hierarchy is a fast data structure and algorithm for localizing data based on a triangle inequality obeying distance metric, the algorithm strives to minimize the number of distance calculations needed to cluster the documents into "anchors'' around reference documents called "pivots''. We extend the original algorithm to increase the amount of available parallelism and consider two implementations: a complex data structure which affords efficient searching, and a simple data structure which requires repeated sorting. The sorting implementation is integrated with a text corpora "Bag of Words'' program and initial performance results of end-to-end document processing workflow are reported.