Text categorization, especially short text categorization, is a difficult and challenging task
since the text data is sparse and multidimensional. In traditional text classification methods …

Document classification presents difficult challenges due to the sparsity and the high
dimensionality of text data, and to the complex semantics of the natural language. The …

Text classification has been widely used to assist users with the discovery of useful
information from the Internet. However, traditional classification methods are based on the …

Document classification provides an effective way to handle the explosive online textual
data. However, in practical classification settings, we face the so-called feature sparsity …

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 …

Short text is usually expressed in refined slightly, insufficient information, which makes text
classification difficult. But we can try to introduce some information from the existing …

Short text classification is a difficult and challenging task in information retrieval systems
since the text data is short, sparse and multidimensional. In this paper, we represent short …

Text representation is a necessary procedure for text categorization tasks. Currently, bag of
words (BOW) is the most widely used text representation method but it suffers from two …

[Objective] This paper aims to improve the performance of text classification systems with the
help of Wikipedia's feature expansion function.[Methods] First, we established the CDF max …

Traditional Open Directory Project (ODP)-based text classification methods use bag-of-
words approach, which only utilizes single words in ODP documents and ignores important …