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 …

Big multimedia data is heterogeneous in essence, that is, the data may be a mixture of
video, audio, text, and images. This is due to the prevalence of novel applications in recent …

Due to its simplicity, efficiency, and efficacy, naive Bayes (NB) has continued to be one of the
top 10 algorithms in the data mining and machine learning community. Of numerous …

Feature Selection (FS) methods alleviate key problems in classification procedures as they
are used to improve classification accuracy, reduce data dimensionality, and remove …

This paper presents a simple and effective density-based outlier detection approach with
local kernel density estimation (KDE). A Relative Density-based Outlier Score (RDOS) is …

Feature selection is the most significant pre-processing activity, which intends to reduce the
data dimensionality for enhancing the machine learning process. The evaluation of feature …

In the last few years, use of social networking sites has been increased tremendously.
Nowadays, social networking sites generate a large amount of data. Millions of people …

With the massive growth of the Internet, text data has become one of the main formats of
tourism big data. As an effective expression means of tourists' opinions, text mining of such …

To understand the dynamic patterns of behaviours and interactions between athletes that
characterize successful performance in different sports is an important challenge for all sport …

Abstract The Naïve Bayes has proven to be a tractable and efficient method for classification
in multivariate analysis. However, features are usually correlated, a fact that violates the …