Language identification (" LI") is the problem of determining the natural language that a
document or part thereof is written in. Automatic LI has been extensively researched for over …

This paper explores the use of machine learning approaches, or more specifically, four
supervised learning Methods, namely Decision Tree (C 4.5), K-Nearest Neighbour (KNN) …

Web is gigantic and being constantly update. Bangla news in web are rapidly grown in the
era of information age where each news site has its own different layout and categorization …

Species identification via DNA barcodes is contributing greatly to current bioinventory efforts.
The initial, and widely accepted, proposal was to use the protein-coding cytochrome c …

Autocompletion and sequence prediction is the basis of any assistance systems. When we
step out to type something, it is much comforting to get a suggestion of the next word or even …

Offering access to information in microblog posts requires successful language
identification. Language identification on sparse and noisy data can be challenging. In this …

This work investigates the task of identifying the language of digitally encoded text.
Automatic methods for language identification have been developed since the 1960s …

In addition to features and methods used in LI, this chapter introduces the notation devised
by Jauhiainen et al. that is used throughout this book to describe LI methods. For easier …

A Bag-of-Words model is widely used to extract the features from text, which is given as input
to machine learning algorithm like MLP, neural network. The dataset considered is movie …

Semantic analysis is the process of extracting meaning of the sentence, from a given
language. From the perspective of computer processing, challenge lies in making computer …