Successful text classification is highly dependent on the representations used. Currently,
most approaches to text classification adopt thebag-of-words' document representation …

Current classification methods are based on the ldquobag of wordsrdquo (BOW)
representation, which only accounts for term frequency in the documents, and ignores …

An Automatic Document Classifier System based on Ontology and the Naíve Bayes
Classifier is proposed in this paper. The main concept is to first establish a keyword …

Ontology can provide a powerful representation of information space and solve many
semantic problems. It is wonderful to apply ontology to text classification. This paper …

To overcome the limitations of traditional text classification approaches based on bag-of-
words representation and to effectively incorporate linguistic knowledge and conceptual …

Ontology-based documents classification method is introduced to solve the problem of
classifier training and not considering semantic relations between words in traditional …

To overcome the limitations of traditional text classification approaches based on bag-of-
words representation and to effectively incorporate linguistic knowledge and conceptual …

The exponential growth of text documents available on the Internet has created an urgent
need for accurate, fast, and general purpose text classification algorithms. However, the" …

Majority of the existing text classification algorithms are based on the “bag of words”(BOW)
approach, in which the documents are represented as weighted occurrence frequencies of …

The use of ontology in order to provide a mechanism to enable machine reasoning has
continuously increased during the last few years. This paper suggests an automated method …