K-tree: Large Scale Document Clustering

Computer Science – Information Retrieval

Scientific paper

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2 pages, SIGIR 2009

Scientific paper

10.1145/1571941.1572094

We introduce K-tree in an information retrieval context. It is an efficient approximation of the k-means clustering algorithm. Unlike k-means it forms a hierarchy of clusters. It has been extended to address issues with sparse representations. We compare performance and quality to CLUTO using document collections. The K-tree has a low time complexity that is suitable for large document collections. This tree structure allows for efficient disk based implementations where space requirements exceed that of main memory.

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