Title :
New module of text classification for IDA system
Author :
Shatovska, Tetyana ; Kamenieva, Iryna ; Tarasov, Iurii
Author_Institution :
Kharkov Nat. Univ. of Radioelectron., Kharkov, Ukraine
Abstract :
In this article we are comparing Data Mining and Machine learning directions in text classification for IDA system. We will compare two high algorithms Chameleon from Data Mining and SVM (Support vector Machine) from Machine learning. Thus, define the best algorithm for text classification and decide to possibility inclusion SVM and using Chameleon for text classification in IDA system.
Keywords :
data mining; learning (artificial intelligence); pattern classification; support vector machines; data mining; machine learning; support vector machine; text classification; Classification tree analysis; Clustering algorithms; Data mining; Machine learning; Machine learning algorithms; Partitioning algorithms; Support vector machine classification; Support vector machines; Text categorization; Unsupervised learning; Chameleon; Data Mining; IDA system; Machine Learning; SVM; Text classification;
Conference_Titel :
CAD Systems in Microelectronics, 2009. CADSM 2009. 10th International Conference - The Experience of Designing and Application of
Conference_Location :
Lviv-Polyana
Print_ISBN :
978-966-2191-05-9
