Classification of Al-Hadith Al-Shareef using data mining algorithm

Manar Alkhatib, Zayed University

Document Type

Conference Proceeding

Source of Publication

Proceedings of the European, Mediterranean and Middle Eastern Conference on Information Systems: Global Information Systems Challenges in Management, EMCIS 2010

Publication Date

12-1-2010

Abstract

In this paper we compared the effectiveness of four different automatic learning algorithms for classifying Al-Hadith Al-Shareef into 8 selective books depending on Sahih BuKhari.The automatic learning algorithms are Rocchio algorithm, K-NN algorithm (K- Nearest Neighbor), Naïve Bayes algorithm and SVM algorithm (Support Vector Machines). We used TF-IDF technique to compute the relative frequency for each word in a particular document. We split the documents of AL-Hadith in such 75% of AL-Hadiths (1350 Hadiths) are used as training data (build the classifier) and the remaining 25% of AL-Hadith (150 Hadiths) are used for testing the accuracy of the resulting models in reproducing the manual category assignments.The average of words in each document is about 5to10 words.

ISBN

9781902316802

Disciplines

Computer Sciences

Keywords

Al-Hadith Al-Shareef, Bayes, Data mining, KNN, Rachio, SVM, Text classification

Scopus ID

84857576478

Indexed in Scopus

yes

Open Access

no

This document is currently not available here.

Share

COinS