K-tree : large scale document clustering
De Vries, Christopher Michael & Geva, Shlomo (2009) K-tree : large scale document clustering. In 32nd international ACM SIGIR Conference on Research and Development in Information Retrieval, 19-23 July 2009, Boston, MA.
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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|Item Type:||Conference Paper|
|Additional Information:||See additional URL to download software.|
|Keywords:||K-tree, k-means, clustering, document clustering, search tree, performance, algorithm|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Pattern Recognition and Data Mining (080109)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > COMPUTATION THEORY AND MATHEMATICS (080200) > Analysis of Algorithms and Complexity (080201)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > LIBRARY AND INFORMATION STUDIES (080700) > Information Retrieval and Web Search (080704)
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Science and Technology|
|Copyright Owner:||Copyright 2009 The Authors|
|Copyright Statement:||(c) 2009 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.|
|Deposited On:||27 Jul 2009 00:06|
|Last Modified:||01 Mar 2012 01:41|
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