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What is Conditional Random Field (CRF)

Chapter 23
Handbook of Research on Web Log Analysis
Learning system for classification often used for labeling sequential data (such as natural language data); as a type of Markov random field, it is an undirected graphical model in which each vertex represents a random variable, whose distribution is to be inferred, and each edge represents a dependency between two variables.
Published in Chapter:
Information Extraction from Blogs
Marie-Francine Moens (Katholieke Universiteit Leuven, Belgium)
Copyright: © 2009 |Pages: 19
DOI: 10.4018/978-1-59904-974-8.ch023
Abstract
This chapter introduces information extraction from blog texts. It argues that the classical techniques for information extraction that are commonly used for mining well-formed texts lose some of their validity in the context of blogs. This finding is demonstrated by considering each step in the information extraction process and by illustrating this problem in different applications. In order to tackle the problem of mining content from blogs, algorithms are developed that combine different sources of evidence in the most flexible way. The chapter concludes with ideas for future research.
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Chapter 11
Patient Data De-Identification: A Conditional Random-Field-Based Supervised Approach
An undirected probabilistic graphic model categorized under statistical modeling method used for structured prediction in machine learning and pattern recognition.
Published in Chapter: Patient Data De-Identification: A Conditional Random-Field-Based Supervised Approach; From: Handbook of Research on Applied Cybernetics and Systems Science
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Chapter 608
Conditional Random Fields for Modeling Structured Data
A CRF is a probabilistic graphical model that is often applied in pattern recognition for structured prediction . Whereas an ordinary classifier predicts a label for a single sample without regard to “neighboring” sample’s labels, a CRF can take the labels of neighboring samples as well as features corresponding to neighboring samples (context) into account while predicting a label for a given sample.
Published in Chapter: Conditional Random Fields for Modeling Structured Data; From: Encyclopedia of Information Science and Technology, Third Edition
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