High Relevance Keyword Extraction facility for Bayesian text classification on different domains of varying characteristic

LH Lee, D Isa, WO Choo, WY Chue - Expert Systems with Applications, 2012 - Elsevier
LH Lee, D Isa, WO Choo, WY Chue
Expert Systems with Applications, 2012Elsevier
High Relevance Keyword Extraction (HRKE) facility is introduced to Bayesian text
classification to perform feature/keyword extraction during the classifying stage, without
needing extensive pre-classification processes. In order to perform the task of keyword
extraction, HRKE facility uses the posterior probability value of keywords within a specific
category associated with text document. The experimental results show that HRKE facility is
able to ensure promising classification performance for Bayesian classifier while dealing …
High Relevance Keyword Extraction (HRKE) facility is introduced to Bayesian text classification to perform feature/keyword extraction during the classifying stage, without needing extensive pre-classification processes. In order to perform the task of keyword extraction, HRKE facility uses the posterior probability value of keywords within a specific category associated with text document. The experimental results show that HRKE facility is able to ensure promising classification performance for Bayesian classifier while dealing with different text classification domains of varying characteristics. This method guarantees an effective and efficient Bayesian text classifier which is able to handle different domains of varying characteristics, with high accuracy while maintaining the simplicity and low cost processes of the conventional Bayesian classification approach.
Elsevier
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