Automatic text classification is the task of organizing documents into pre-determined classes,
generally using machine learning algorithms. Generally speaking, it is one of the most …

Abstract Vector Space Models (VSM) are commonly used in language processing to
represent certain aspects of natural language semantics. Semantics of VSM comes from the …

In this study, we propose a novel methodology to build a semantic smoothing kernel to use
with Support Vector Machines (SVM) for text classification. The suggested approach is …

Automated classification is usually not adjusted to specialized domains due to a lack of
suitable data collections and insufficient characterization of the domain‐specific content and …

The study of semantic kernel function is an important branch of kernel function research in
recent years. However, there are few studies on the use of semantic kernel function in …

Due to the huge size of the data accumulated on microblogging sites, recently, two
fundamental questions have become very popular: 1) What percentage of this accumulated …

In text categorization, a document is usually represented by a vector space model which can
accomplish the classification task, but the model cannot deal with Chinese synonyms and …

The purpose of this study is to show the success of Abstract Feature Extraction Method in
multi dimensional feature vectors studies. Author recognition study is taken as an application …

Due to the increased level of the big-sized documents in recent years, dimensionality
reduction has become a significant step in the text document processing and classification …

Compared to traditional networking which using command-line interfaces, intent-based
networking abstracts network complexity and improves automation by eliminating manual …