scholarly journals Activity Discovery Using Compressed Suffix Trees

2011 ◽  
pp. 69-78 ◽  
Author(s):  
Prithwijit Guha ◽  
Amitabha Mukerjee ◽  
K. S. Venkatesh
Keyword(s):  
Suffix Trees ◽  
Activity Discovery

Analysis of Markov Models

2013 ◽  
Vol 462-463 ◽  
pp. 243-246
Author(s):  
Chang Guang Shi
Keyword(s):  
Markov Models ◽  
Suffix Trees

Highly-available models and IPv4 have garnered improbable interest from both statisticians and experts in the last several years. Here, we show the emulation of suffix trees. We motivate an algorithm for suffix trees, which we use to demonstrate that e-business and replication can interact to solve this challenge.

An Online Pattern Based Activity Discovery: In Context of Geriatric Care

2019 ◽  
pp. 25-38
Author(s):  
Moumita Ghosh ◽  
Sayan Chatterjee ◽  
Shubham Basak ◽  
Sankhayan Choudhury
Keyword(s):  
Geriatric Care ◽  
Activity Discovery

scholarly journals On the Number of 2-Protected Nodes in Tries and Suffix Trees

2012 ◽  
Vol DMTCS Proceedings vol. AQ,... (Proceedings) ◽  
Author(s):  
Jeffrey Gaither ◽  
Yushi Homma ◽  
Mark Sellke ◽  
Mark Daniel Ward
Keyword(s):  
Suffix Trees ◽  
First Order ◽  
International Audience

International audience We use probabilistic and combinatorial tools on strings to discover the average number of 2-protected nodes in tries and in suffix trees. Our analysis covers both the uniform and non-uniform cases. For instance, in a uniform trie with $n$ leaves, the number of 2-protected nodes is approximately 0.803$n$, plus small first-order fluctuations. The 2-protected nodes are an emerging way to distinguish the interior of a tree from the fringe.

Graphical pan-genome analysis with compressed suffix trees and the Burrows–Wheeler transform

2015 ◽  
Vol 32 (4) ◽  
pp. 497-504 ◽  
Author(s):  
Uwe Baier ◽  
Timo Beller ◽  
Enno Ohlebusch
Keyword(s):  
Genome Analysis ◽  
Suffix Trees ◽  
Pan Genome ◽  
Burrows Wheeler Transform
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