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Tree visualization with Tree-maps: A 2-d space-filling approach

by Ben Shneiderman - ACM Transactions on Graphics , 1991
"... this paper deals with a two-dimensional (2-d) space-filling approach in which each node is a rectangle whose area is proportional to some attribute such as node size. Research on relationships between 2-d images and their representation in tree structures has focussed on node and link representation ..."
Abstract - Cited by 534 (29 self) - Add to MetaCart
this paper deals with a two-dimensional (2-d) space-filling approach in which each node is a rectangle whose area is proportional to some attribute such as node size. Research on relationships between 2-d images and their representation in tree structures has focussed on node and link

Mining Frequent Patterns without Candidate Generation: A Frequent-Pattern Tree Approach

by Jiawei Han, Jian Pei, Yiwen Yin, Runying Mao - DATA MINING AND KNOWLEDGE DISCOVERY , 2004
"... Mining frequent patterns in transaction databases, time-series databases, and many other kinds of databases has been studied popularly in data mining research. Most of the previous studies adopt an Apriori-like candidate set generation-and-test approach. However, candidate set generation is still co ..."
Abstract - Cited by 1752 (64 self) - Add to MetaCart
costly, especially when there exist a large number of patterns and/or long patterns. In this study, we propose a novel frequent-pattern tree (FP-tree) structure, which is an extended prefix-tree structure for storing compressed, crucial information about frequent patterns, and develop an efficient FP-tree

Treemaps: a space-filling approach to the visualization of hierarchical information structures

by Brian Johnson, Ben Shneiderman - PROC. 2ND INTERNATIONAL VISUALIZATION CONFERENCE 1991. IEEE , 1991
"... This paper describes a novel method for the visualization of hierarchically structured information. The Tree-Map visualization technique makes 100 % use of the available display space, mapping the full hierarchy onto a rectangular region in a space-filling manner. This efficient use of space allows ..."
Abstract - Cited by 476 (26 self) - Add to MetaCart
This paper describes a novel method for the visualization of hierarchically structured information. The Tree-Map visualization technique makes 100 % use of the available display space, mapping the full hierarchy onto a rectangular region in a space-filling manner. This efficient use of space allows

Comparison of discrimination methods for the classification of tumors using gene expression data

by Sandrine Dudoit, Jane Fridlyand, Terence P. Speed - JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION , 2002
"... A reliable and precise classification of tumors is essential for successful diagnosis and treatment of cancer. cDNA microarrays and high-density oligonucleotide chips are novel biotechnologies increasingly used in cancer research. By allowing the monitoring of expression levels in cells for thousand ..."
Abstract - Cited by 770 (6 self) - Add to MetaCart
A reliable and precise classification of tumors is essential for successful diagnosis and treatment of cancer. cDNA microarrays and high-density oligonucleotide chips are novel biotechnologies increasingly used in cancer research. By allowing the monitoring of expression levels in cells

Nonparametric model for background subtraction

by Ahmed Elgammal, David Harwood, Larry Davis - in ECCV ’00 , 2000
"... Abstract. Background subtraction is a method typically used to seg-ment moving regions in image sequences taken from a static camera by comparing each new frame to a model of the scene background. We present a novel non-parametric background model and a background subtraction approach. The model can ..."
Abstract - Cited by 545 (17 self) - Add to MetaCart
Abstract. Background subtraction is a method typically used to seg-ment moving regions in image sequences taken from a static camera by comparing each new frame to a model of the scene background. We present a novel non-parametric background model and a background subtraction approach. The model

Quartet puzzling: a quartet maximum likelihood method for reconstructing tree topologies.

by Korbinian Strimmer , Arndt Von Haeseler - Mol. Biol. Evol. , 1996
"... A versatile method, quartet puzzling, is introduced to reconstruct the topology (branching pattern) of a phylogenetic tree based on DNA or amino acid sequence data. This method applies maximum-likelihood tree reconstruction to all possible quartets that can be formed from n sequences. The quartet t ..."
Abstract - Cited by 433 (9 self) - Add to MetaCart
A versatile method, quartet puzzling, is introduced to reconstruct the topology (branching pattern) of a phylogenetic tree based on DNA or amino acid sequence data. This method applies maximum-likelihood tree reconstruction to all possible quartets that can be formed from n sequences. The quartet

Geometry Compression

by Michael Deering
"... This paper introduces the concept of Geometry Compression, allowing 3D triangle data to be represented with a factor of 6 to 10 times fewer bits than conventional techniques, with only slight losses in object quality. The technique is amenable to rapid decompression in both software and hardware imp ..."
Abstract - Cited by 350 (0 self) - Add to MetaCart
triangles. Then a variable length compression is applied to individual positions, colors, and normals. Delta compression followed by a modified Huffman compression is used for positions and colors; a novel table-based approach is used for normals. The table allows any useful normal to be represented

An optimal graph theoretic approach to data clustering: Theory and its application to image segmentation

by Zhenyu Wu, Richard Leahy - IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE , 1993
"... A novel graph theoretic approach for data clustering is presented and its application to the image segmentation problem is demonstrated. The data to be clustered are represented by an undirected adjacency graph G with arc capacities assigned to reflect the similarity between the linked vertices. Cl ..."
Abstract - Cited by 360 (0 self) - Add to MetaCart
A novel graph theoretic approach for data clustering is presented and its application to the image segmentation problem is demonstrated. The data to be clustered are represented by an undirected adjacency graph G with arc capacities assigned to reflect the similarity between the linked vertices

The benefits of coding over routing in a randomized setting

by Tracey Ho, Ralf Koetter, Muriel Médard, David R. Karger, Michelle Effros - In Proceedings of 2003 IEEE International Symposium on Information Theory , 2003
"... Abstract — We present a novel randomized coding approach for robust, distributed transmission and compression of information in networks. We give a lower bound on the success probability of a random network code, based on the form of transfer matrix determinant polynomials, that is tighter than the ..."
Abstract - Cited by 361 (44 self) - Add to MetaCart
Abstract — We present a novel randomized coding approach for robust, distributed transmission and compression of information in networks. We give a lower bound on the success probability of a random network code, based on the form of transfer matrix determinant polynomials, that is tighter than

Geometric Compression through Topological Surgery

by Gabriel Taubin, Jarek Rossignac - ACM TRANSACTIONS ON GRAPHICS , 1998
"... ... this article introduces a new compressed representation for complex triangulated models and simple, yet efficient, compression and decompression algorithms. In this scheme, vertex positions are quantized within the desired accuracy, a vertex spanning tree is used to predict the position of each ..."
Abstract - Cited by 283 (28 self) - Add to MetaCart
... this article introduces a new compressed representation for complex triangulated models and simple, yet efficient, compression and decompression algorithms. In this scheme, vertex positions are quantized within the desired accuracy, a vertex spanning tree is used to predict the position of each
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