The aim of this study is to provide an overview the state-of-the-art elements of text
classification. For this purpose, we first select and investigate the primary and recent studies …

Many real-world text classification tasks often deal with a large number of closely related
categories organized in a hierarchical structure or taxonomy. Hierarchical multi-label text …

Over recent years, the emergence of electronic text processing systems has generated a
vast amount of structured and unstructured data, thus creating a challenging situation for …

In order to improve the text matching degree and calculation accuracy of the short text
classification method, this paper studies the optimization of the short text classification …

In the Web 2.0 era, the problem of uneven quality and overload of online reviews is very
serious, and the cognitive cost of obtaining valuable content from them is getting higher and …

The IDF (Inverse Document Frequency) term weighting method is a classic treatment of a
term's significance in information retrieval and text analytics. IDF can be derived from the …

The literature has reported that hierarchical classification methods generally outperform the
flat classification methods for a multi-class document classification problem. Unlike the …

Some business license commitments in online single submission (OSS) currently only
consist of an independent statement from the business actor, and there is no time limit for …

In the era of big data, the importance of data classification is increasing. However, when it
comes to classifying text documents, several obstacles degrade classification performance …

The Discounted Least Information Theory of Entropy (DLITE) is a new information measure
that quantifies the amount of entropic difference between two probability distributions. It …