Classification of Multiple Emotions in Indonesian Text Using The K-Nearest Neighbor Method

An Improved K-Nearest Neighbor with Crow Search Algorithm for Feature Selection in Text Documents Classification

The Internet provides easy access to a kind of library resources. However, classification of documents from a large amount of data is still an issue and demands time and energy to find certain documents. Classification of similar documents in specific classes of data can reduce the time for searching the required data, particularly text documents. This is further facilitated by using Artificial...

An Improved K-Nearest Neighbor with Crow Search Algorithm for Feature Selection in Text Documents Classification

The Internet provides easy access to a kind of library resources. However, classification of documents from a large amount of data is still an issue and demands time and energy to find certain documents. Classification of similar documents in specific classes of data can reduce the time for searching the required data, particularly text documents. This is further facilitated by using Artificial...

Classification of Emotions in Indonesian Texts Using K-nn Method

This paper aims to classify texts in Indonesian language into emotion expression classes. The data were taken from 6 basic emotion classes whose training documents and test documents were obtained from articles in www.kompas.com, www.suaramerdeka.com, and www.detik.com. The text weighing was processed by using TFID method which is an integration of Term Frequency (TF) and Inverse Document Frequ...

Text Categorization Using Weight Adjusted k-Nearest Neighbor Classification

Text categorization is the task of deciding whether a document belongs to a set of prespecified classes of documents. Automatic classification schemes can greatly facilitate the process of categorization. Categorization of documents is challenging, as the number of discriminating words can be very large. Many existing algorithms simply would not work with these many number of features. k-neares...

F-term Classification System Using K-Nearest Neighbor Method