Classification is the grouping of information or objects in predefined labeled categories
based on similarities. Exponential growth rates of scientific document collection leads to …

Document classification is an important task in data mining. Currently, identifying category
(ie, topic) of a scientific publication is a manual task. The Association for Computing …

Traditional TF-IDF (Term Frequency-Inverse Document Frequency) feature weighting
algorithm only uses word frequency information as a measure of the importance of feature …

Since, electronic documents are dramatically increasing therefore document classification
becomes a very important task to organise inormation automatically. Text documents are a …

The feature weight algorithm of the text can calculate the classification accuracy of the entire
text. The traditional tf-idf (Term Frequency Inverse Document Frequency) algorithm is only …

News articles categorization is a supervised learning approach in which news articles are
assigned category labels based on likelihood demonstrated by a training set of labeled …

Text Classification (TC) is a popular information retrieval (IR) technique that mainly employs
features selection, features reduction, and features weighting techniques. The most common …

Aiming at the characteristic of text categorization, this paper proposes an improved method
of computing term weights, tfidfie, based on the traditional tfidf function that is generally used …

Most of traditional text classification methods utilize term frequency (tf) and inverse
document frequency (idf) for representing importance of terms and computing weighting of …

Text Categorization is the process of automatically assigning predefined categories to free
text documents. Feature weight, which calculates feature (term) values in documents, is one …