Variable length Markov chains

Variable Length Markov Chains

We study estimation in the class of stationary variable length Markov Ž . chains VLMC on a finite space. The processes in this class are still Markovian of high order, but with memory of variable length yielding a much bigger and structurally richer class of models than ordinary highorder Markov chains. From an algorithmic view, the VLMC model class has attracted interest in information theory ...

Variable length Markov chains and dynamical sources

Infinite random sequences of letters can be viewed as stochastic chains or as strings produced by a source, in the sense of information theory. The relationship between Variable Length Markov Chains (VLMC) and probabilistic dynamical sources is studied. We establish a probabilistic frame for context trees and VLMC and we prove that any VLMC is a dynamical source for which we explicitly build th...

Text Mining Using Markov Chains of Variable Length

When dealing with knowledge federation over text documents one has to gure out whether or not documents are related by context. A new approach is proposed to solve this problem. This leads to the design of a new search engine for literature research and related problems. The idea is that one has already some documents of interest. These documents are taken as input. Then all documents known to ...

Learning Variable Memory Length Markov Chains from Noisy Output

Variable Length Markov Chains for Web Usage Mining

Web usage mining is usually defined as the discipline that concentrates on developing techniques that model and study users’ Web navigation behavior by means of analyzing data obtained from user interactions with Web resources; see (Mobasher, 2006; Liu, 2007) for recent reviews on web usage mining. When users access Web resources they leave a trace behind that is stored in log files, such trace...