Work

Random Indexing K-tree

Year: 2010

Type: preprint

Abstract: 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.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.1001.0833

Authors: De Vries, Christopher M., De Vine, Lance, Geva, Shlomo

Institution: Queensland University of Technology

Language: English

Topic: Advanced Clustering Algorithms Research

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W2138128302

Cites:

Cited by: 1

Related to: 20