FORUM BASED DATA MINING TOOL FOR TEACHING LEARNING EXPERIENCE

Govindraj B. Chittapur , Veena B. Desai

Abstract Today we are living in a social media world, we use to give much information to the social forum, by referring as twitter information as social forum and identifying teaching learning experience through given set of information. Students’ informal conversations on social media shed light into their educational experiences opinions, feelings, and concerns about the learning process. Data from such un-instrumented environments can provide valuable knowledge to inform student learning. We used Navie Bayes multi classifier algorithm used for classify tweet based student opinion about teaching learning experience even by using Maximum likelihood method is used to computer and compare classifier result. Keywords: Data Mining, Forum, Navie-Bayes, Maximum-Likelihood, Stop words, Student problems, Probability computation,

Title:	FORUM BASED DATA MINING TOOL FOR TEACHING LEARNING EXPERIENCE
Author Name:	Govindraj B. Chittapur , Veena B. Desai
Abstract:	Abstract Today we are living in a social media world, we use to give much information to the social forum, by referring as twitter information as social forum and identifying teaching learning experience through given set of information. Students’ informal conversations on social media shed light into their educational experiences opinions, feelings, and concerns about the learning process. Data from such un-instrumented environments can provide valuable knowledge to inform student learning. We used Navie Bayes multi classifier algorithm used for classify tweet based student opinion about teaching learning experience even by using Maximum likelihood method is used to computer and compare classifier result. Keywords: Data Mining, Forum, Navie-Bayes, Maximum-Likelihood, Stop words, Student problems, Probability computation,
Cite this article:	Govindraj B. Chittapur , Veena B. Desai , " FORUM BASED DATA MINING TOOL FOR TEACHING LEARNING EXPERIENCE " , International Journal of Emerging Trends & Technology in Computer Science (IJETTCS), Volume 6, Issue 4, July - August 2017 , pp. 072-076 , ISSN 2278-6856.
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