Random Indexing (RI) K-tree is the combination of two algorithms for
clustering. Many large scale problems exist in document clustering. RI K-tree
scales well with large inputs due to its low complexity. It also exhibits
features that are useful for managing a changing collection. Furthermore, it
solves previous issues with sparse document vectors when using K-tree. The
algorithms and data structures are defined, explained and motivated. Specific
modifications to K-tree are made for use with RI. Experiments have been
executed to measure quality. The results indicate that RI K-tree improves
document cluster quality over the original K-tree algorithm.Comment: 8 pages, ADCS 2009; Hyperref and cleveref LaTeX packages conflicted.
Removed clevere
