Searching for "Review of "Introduction to clustering large and high-dimensional data" by J. Kogan." – sorted by Relevance.
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Modeling of High-Dimensional Data
- 5 A, FIN-02150 Espoo, Finland Chapter 8 Modeling of high-dimensional data Heikki Hyotyniemi
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High-dimensional Similarity Joins
- data mining applications require efficient processing of similarity joins on high-dimensional points
- Cited by 29 (2 self) – Add To MetaCart
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Clustering In A High-Dimensional Space Using
- Clustering In A High-Dimensional Space Using Hypergraph Models # Eui-Hong (Sam) Han George Karypis
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Learning to Visualise High-Dimensional Data
- Learning to Visualise High-Dimensional Data Khurshid Ahmad, Bogdan Vrusias Dept. of Computing
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Class Visualization of High-Dimensional Data with Applications
- the relevant literature on visualizing high-dimensional data; for a broad review of the field, see, for example
- Cited by 12 (0 self) – Add To MetaCart
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Towards High-Dimensional Clustering
- size data sets, the cluster-ordering information can be represented graphically. Very large high-dimensional
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Indexing Regional Objects in High-Dimensional Spaces
- . INTRODUCTION There is a large body of literature on accessing data in high-dimensional spaces: Berchtold, Bohm
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Parallel Algorithms for High-dimensional Proximity Joins
- such as polygons and line segments and are not well optimized for handling high-dimensional point data. We examine
- Cited by 15 (0 self) – Add To MetaCart
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Learning High-Dimensional Data
- , Siena (Italy), 22-24 October 2001, 22 pp. 1. Introduction Learning high-dimensional data Michel
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Image registration methods in high-dimensional space
- Image registration methods in high-dimensional space Huzefa Neemuchwala a,c , Alfred Hero a
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