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 …

The automated categorization (or classification) of texts into predefined categories has
witnessed a booming interest in the last 10 years, due to the increased availability of …

The problem of classification has been widely studied in the data mining, machine learning,
database, and information retrieval communities with applications in a number of diverse …

Text categorization is widely used when organizing documents in a digital form. Due to the
increasing number of documents in digital form, automated text categorization has become …

Support vector machine is a classification model which has been widely used in many
nonlinear and high dimensional pattern recognition problems. However, it is inefficient or …

As the Web continues to grow, it has become increasingly difficult to search for relevant
information using traditional search engines. Topic-specific search engines provide an …

Forecasting future trends of the stock market using the historical data is the exigent demand
in the field of academia as well as business. This work has explored the feature optimization …

Sentiment analysis becomes very useful since the rise of social media and online review
website and, thus, the requirement of analyzing their sentiment in an effective and efficient …

In this work we investigate the usefulness of n-grams for document indexing in text
categorization (TC). We call n-gram a set gk of n word stems, and we say that gk occurs in a …

Artificial neural networks are computer software or hardware models inspired by the
structure and behavior of neurons in the human nervous system. As a powerful learning tool …