DATA MINING FOR HADITH CLASSIFICATION BY KAWTHER …

DATA MINING FOR HADITH CLASSIFICATION

BY

KAWTHER A.ALDHLAN

A thesis submitted in fulfilment of the requirement

for the degree of Doctor of Philosophy in Information and

Communication Technology

Kulliyyah of Information and

Communication Technology

International Islamic University

Malaysia

FEBRUARY 2013

ii

ABSTRACT

The holy Qur'an and Hadith are the two fundamental resources of the legislation and

law in Muslim community. Including the Islamic books, these resources can be used

as the sole authoritative source of knowledge and wisdom. Besides, they stand out as

the source of a large collection of analysis and interpretation texts, which could

provide a gold standard for artificial intelligent (AI) knowledge extraction and

knowledge representation experiments. Recently, there are increasing attentions to

automate the Islamic resources Qur'an, Sunnah and tradition books, motivate

researchers to look for mechanisms that can represent and discover the knowledge of

these resources. In the present study, extracted Islamic knowledge representing the

focal point of the research, three famous books in Hadith science framed the corpus of

this study. The present study attempted to explore new approach to classify Hadith

according to its validity degree (Sahih, Hasan, Da'eef and Maudoo') using data mining

techniques, the proposed Hadith classifier (HC) model was built through learning

process and was represented by the tree structure modeling. Moreover, the attributes

of the instances originally were obtained from the source books directly. Whilst some

of these attributes which is not mentioned in these books were indicated as null

values, or missing values. A novel mechanism was employed to handle these missing

data. This mechanism was generated based on the investigation methods of the Isnad

in Hadith science. Representing or extracting Islamic knowledge is very critical step

because it may affect life of Muslim, therefore, the results of the research were

compared with the resource books, concurrently with the point of view of the expert in

Hadith science. Indeed, the extracted knowledge shed light on the differences between

Al-Imam Al-Bukhari, Al-Termithi and Al-Albani methods in takhareej AL-Hadith. Furthermore, the findings of the research showed that the performance of the proposed

HC had significant effect with the proposed missing data detector method (MDD), the

correct classification rate (CCR) was sharply increased from (50.1502 %) before using

MDD to (97.597%) after applying it . Furthermore, the favorable results of comparing

the performance of HC against naïve bayes classifier indicated that the decision tree

(DT) Modeling is a viable approach to classify Hadith due to the excel performance,

ease of implementation, and ease of rules induction and results interpretation.

iii

HC

HC

MDDCCR

MDD

iv

APPROVAL PAGE

The thesis of Kawther Binti Ali ALdhlan has been approved by the following:

___________________________ Akram M. Zeki

Supervisor

___________________________ Ahmed M. Zeki

Co-Supervisor

___________________________ Tengku Mohd Bin Tengku Sembok

Internal Examiner

___________________________ Imad Fakhri Taha Alshaikhli

Internal Examiner

___________________________ Hassanin M. Al-Barhamtoshy

External Examiner

___________________________ Abdul Kabir Hussain Solihu

Chairman

v

DECLARATION

I hereby declare that this thesis is the result of my own investigations, except where

otherwise stated. I also declare that it has not been previously or concurrently

submitted as a whole for any other degrees at IIUM or other institutions.

Kawther Binti Ali Dhlan Al-Dhlan

Signature …………………………………… Date ……………………..

vi

INTERNATIONAL ISLAMIC UNIVERSITY MALAYSIA

DECLARATION OF COPYRIGHT AND AFFIRMATION

OF FAIR USE OF UNPUBLISHED RESEARCH

Copyright © 3102 by Kawther Binti Ali Al-Dhlan. All rights reserved.

DATA MINING FOR HADITH CLASSIFICATION

No part of this upublished research may be reproduced, stored in a retrieval system, or

transmitted, in any form or by any means, electronic, mechanical, photocopying,

recording or otherwise without prior written permission of the copyright holder except

as provided below.

1. Any material contained in or derived from this unpublished research may

only be used by others in their writing with due acknowledgement.

2. IIUM or its library will have the right to make and transmit copies (print

or electronic) for institutional and academic purposes.

3. The IIUM library will have the right to make, store in a retrieval system

and supply copies of this unpublished research if requested by other

universities and research libraries.

Affirmed by Kawther Binti Ali Dhlan Aldhlan.

…………………………. ………………..

Signature Date

vii

To My Beloved Mother (May Allah Bless Her)

To My Father

To My Husband and My Family

viii

ACKNOWLEDGEMENTS

In the name of Allah, the Most Beneficent, the Most Merciful.

All praise and gratitude to Almighty Allah S.W.T. for giving me an opportunity to

undertake and complete this study.

I felt very grateful for having an exceptional doctoral committee. Without their

guidance and support, I may not be able to reach this far in my academic endeavor.

First and foremost, my deepest gratitude goes to Dr. Akram M. Zeki, my major

supervisor and my mentor. His dedication and patient in guiding me has helped me

get through this study and make me what I am today. My deepest gratitude also goes

to Dr. Ahmed M. Zeki, my co-supervisor, who have greatly contributed in assisting

me to complete my work. I would to extent my thanks to the examiners committee for

their valued notes.

My personal thanks also go to all lecturers and staff of the Kulliyyah of

Information and Communication Technology whose wisdom have shaped my way of

looking at things one way or another.

I am also grateful to the University Of Hail UOH for giving me this priceless

opportunity to further my study in this doctoral program. And special thanks to

Associate Prof. Dr. Naser Ismail from Islamic department in college of education in

UOH for his efforts and guidance.

Finally, I would like to extend my gratitude to my beloved husband, Hamad

Alreshidi, for his understanding, collaborative and undivided support. To my children,

Solaf, Turki and Wed may this success become an inspiration for their future. And to

my mother (God bless her), father, sisters and brothers thank you for your unfailing

faith, thank you for encouragements and prayers.

ix

TABLE OF CONTENTS

Abstract ................................................................................................................... ii

Abstract in Arabic .................................................................................................... iii

Approval Page .......................................................................................................... v

Declaration Page ...................................................................................................... vi

Copyright Page ......................................................................................................... vii

Dedication ................................................................................................................ viii

Acknowledgement ................................................................................................... ix

List of Tables .......................................................................................................... xiii

List of Figures ......................................................................................................... xv

List of Abbreviations .............................................................................................. xviii

List of Symbols ........................................................................................................ xxi

CHAPTER ONE: INTRODUCTION ................................................................. 1

1.1 The Importance of Hadith ................................................................... 1

1.2 Background of the Study ........................................................................ 3

1.3 Statement of the Problem ....................................................................... 8

1.4 Research Objectives .............................................................................. 10

1.5 Research Questions ................................................................................ 10

1.6 Research Hypotheses ............................................................................. 11

1.7 Significance of the Study ....................................................................... 11

1.8 Research Model ...................................................................................... 12

1.8.1 The Research Framework ........................................................... 12

1.8.2 Data Representation Models ........................................................ 14

1.8.2.1 Hadith Structure ............................................................... 14

1.8.2.2 The Representation of Hadith Structure ............................ 15

1.9 Research Approach ............................................................................... 16

1.10 Organization of the Thesis ................................................................... 17

CHAPTER TWO: OVERVIEW OF HADITH SCIENCE ............................... 19

2.1 Introduction ............................................................................................ 19

2.2 Definition of Hadith ............................................................................... 20

2.3 Component of Hadith ........................................................................... 20

2.4 Hadith Verification ............................................................................... 22

2.5 Classification of Hadith ........................................................................ 24

2.6 Summary ............................................................................................... 33

CHAPTER THREE: LITRATURE REVIEW ................................................... 35

3.1 Introduction ............................................................................................ 35

3.2 Overview of Data Mining ...................................................................... 35

3.2.1 What Is a Data Mining? ............................................................... 35

3.2.2 Data Mining Approaches ............................................................. 37

3.2.2.1 Supervised learning ........................................................... 37

x

3.2.2.2 Unsupervised Clustering .................................................... 45

3.2.2.3 Semi-supervised learning ................................................... 46

3.2.3 How to Mine Data ........................................................................ 46

3.2.3.1 The Knowledge Discovery Process .................................. 47

3.2.4 Applications of Data Mining ........................................................ 51

3.2.5 Why Data Mining ............................................................................ 57

3.3 The role of ICT in Islam ................................................................................... 58

3.4 Applications of DM in Hadith Science .................................................. 60

3.5 Summary ................................................................................................ 67

CHAPTER FOUR: RESEARCH METHODOLOGY ....................................... 68

4.1 Introduction ............................................................................................ 68

4.2 Research Framework .............................................................................. 68

4.3 Research Procedures .............................................................................. 72

4.4 The Sample of the Study ........................................................................ 81

4.5 Evaluation Strategy ................................................................................ 84

4.5.1 Confusion Matrix ......................................................................... 84

4.5.2 Correct Classification Rate .......................................................... 85

4.5.3 Error Rate ..................................................................................... 86

4.5.4 Sensitivity ..................................................................................... 86

4.5.5 Specificity ................................................................................... 87

4.5.6 Precision ....................................................................................... 87

4.5.7 F-Measure .................................................................................. 87

4.5.8 Receiver Operating Characteristic .............................................. 88

4.5.9 Area under the Curve ................................................................... 90

4.6 Summary ................................................................................................ 90

CHAPTER FIVE: DATA PRE-PROCESSING AND ALGORITHMS ........... 92

5.1 Introduction ........................................................................................... 92

5.2 Corpus of the Study ............................................................................... 92

5.3 Data Pre-Processing ............................................................................... 94

5.4 Attributes Selection ............................................................................... 95

5.5 The Missing Data Detector Method (MDD) .......................................... 98

5.6 Decision Tree Construction ................................................................... 113

5.6.1 Select the Attributes .................................................................... 114

5.6.1.1 Entropy (Information Impurity) ......................................... 114

5.6.1.2 Information Gain Criterion ................................................ 115

5.6.1.3 Gain ratio ........................................................................... 116

5.6.2 Pruning Option ............................................................................. 116

5.6.2.1 Pre-Pruning ........................................................................ 117

5.6.2.2 Post-Pruning ....................................................................... 117

5.6.2.3 Comparisons of pre-pruning and post-pruning .................. 117

5.6.3 Rule Induction Based on the Pruned Tree.................................... 119

5.7 C4.5 Algorithm ..................................................................................... 119

5.8 Summary ............................................................................................... 120

xi

CHAPTER SIX: MODEL EVALUATION AND DISCUSSION ..................... 121

6.1 Introduction ............................................................................................ 121

6.2 Implementation ...................................................................................... 122

6.3 Experiment Procedures .......................................................................... 122

6.3.1 Training Procedures ..................................................................... 122

6.3.2 Testing Procedures ....................................................................... 129

6.3.2.1 Trial#1: Test Phase with (33.3%) of the Sample size ........ 129




6.3.3 Comparing the Results of HC with the Expert Point View ......... 144

6.4 The Comparison between the HC and Naïve Bayes Classifier .............. 146

6.5 Summary ............................................................................................... 149

CHAPTER SEVEN: CONCLUSION AND FUTURE WORKS ....................... 151

7.1 Overview ............................................................................................... 151

7.2 Summary of the proposed method ........................................................ 151

7.3 Summary of Findings ............................................................................. 153

7.4 Comparative study with literature ......................................................... 154

7.5 Conclusion .............................................................................................. 156

7.6 Contributions .......................................................................................... 157

7.7 Future Directions .................................................................................... 158

BIBLIOGRAPHY ................................................................................................. 160

APPENDIX A ......................................................................................................... 169

GLOSSARY ............................................................................................................ 175

xii

LIST OF TABLES

Table No. Page No.

3.1 Summarization of the previous works in Hadith 65

4.1 The attributes of the sample set 76

4.2 No. of Hadith in Al-Bukhari collection 81

4.3 Al-Bukhari narrators' grade 82

4.4 Confusion matrix 85

4.5 AUC index and its effectiveness for discrimination 90

5.1 Results of pre-processing phase for Al-Hadith in Figure 5.4 95

5.2 Hadith attributes according to (Al-Suyutih, 1965,Tahan,1996) 97

5.3 The Tracing Table of the Example (1) 103

5.4 Hadith terms used to indicate the narrator's reliability 104


5.6 Hadith terms used to indicate the narrator's retention (preservation) 108



5.9 The rank of the attributes according to the entropy value 115

5.10 The rank of the attributes according to the information gained Method 115

5.11 The rank of the attributes according to gain ratio method 116

6.1 The information gained of the Hadith features 123

6.2 The evaluation results of Hadith Classifier (training phase) 127

6.3 The evaluation results of HC of trial#1 131



xiii


6.7 The RS Between the Results of HC and the Expert Point View 145

6.8 The comparison between Naïve Bayes classifier and HC classifier 146

7.1 Comparative Study with the literature 155

xiv

LIST OF FIGURES

Figure No. Page No.

1.1 The research framework 12

1.2 The proposed Hadith Classifier HC 13

1.3 Hadith components 14

1.4 Bottom- Up approach 15

1.5 Top- Down approach 15

2.1 Components of Hadith 21

2.2 Hadith classification 24

2.3 Mursal مُرْسَل (hurried) case 26

2.4 Munqati’ مُنْقَطِع (broken) case 26

2.5 Mu’allaq مُعَلَق (hanging) case 27

3.1 The boundary hyperplane in support vector machine 39

3.2 Illustration of decision tree with replication 43

3.3 An overview of the knowledge discovery process (KDP) 50

4.1 Hadith classification without handling missing data 69

4.2 The process of missing data detector MDD 70

4.3 The proposed Hadith Classifier 71

4.4 The research procedures 73

4.5 The first stage of the experiment (Training phase) 78

4.6 The second stage of the experiment (Testing phase I) 79

4.7 The second stage of the experiment (Testing phase II) 80

4.8 AL-Ahadith in Sahih Al-Bukhari 81

4.9 Summary of Al-Bukhari narrators' grade 82

xv

4.10 AL-Ahadith in Jami'u AL-Termithi 83

4.11 AL-Ahadith in Silsilat Al-AHadith Al-Dae'ifah w' Al-Mawdu'ah. 83

4.12 The confusion matrix of the training model 85

4.13 An ROC curve and different points of significance 89

5.1 Example of Sahih Hadith 93

5.2 Example of Hasan Hadith 93

5.3 Example of Da'eef Hadith 93

5.4 Example of Maudoo' Hadith 93

5.5 The metadata of the Hadith narrators in narrator table 99

5.6 The relationships between the narrators in the teacher table 99

5.7 The flowchart of the first method 100

5.8 The flowchart of the second method 102

5.9 The flowchart of the narrators' reliability method (Part I) 106

5.10 The flowchart of the narrators 'reliability method (Part II) 107

5.11 The flowchart of the method of determining the narrator's

preservation 110

5.12 The flowchart of the method that determines the value of the Isnad

defective 112

5.13 Part of DT tree for HC 118

6.1 The results of identification narrators of the Isnad chain 124

6.2 The induced rules after parsing the path from the root to the leaf node 124

6.3 The decision tree of the target Hadith Classifier 125

6.4 The confusion matrix of the training model 126

6.5 ROC curves of the classes in Hadith classifier (Training Phase) 128

6.6 Test procedures 129

6.7 The confusion matrix of Hadith Classifier of trial#1 130

xvi

6.8 ROC curves of the classes in HC for trial#1 132

6.9 Isnad identification Process for 33.3% of test dataset 134

6.10 Classification process of 33.3% of test dataset 135





6.15 Isnad identification process for trial#4 140

6.16 Classification process of trial#4 141


6.18 ROC curves of the classes in Hadith Classifier for trial#4 143

6.19 ROC curves of the naïve Bayes classifier 148

6.20 CCR of naïve Bayes classifier and DT classifier 149

7.1 Summary of the research approach 152

xvii

LIST OF ABBREVIATIONS

Acc Accurate rate

ANN Artificial Neural Network

AUC Area Under the Curve

CART Classification And Regression Trees

CBR Case-Based Reasoning

CCR Correct Classification Rate

CCRE Correct Classification Rate according to the Expert

CCRHC Correct Classification Rate according to the HC.

DFT Document Frequency Thresholding

DM Data Mining

DOB Date Of Birth

DOD Date Of Death

DTs Decision Trees

ER Error Rate

FN False Negative

FP False Positive

GA Genetic Algorithms

HC Hadith Classifier

ICT Information Communication Technology

ID Identification

ID3 Interactive Dicotomizer

KDP Knowledge Discovery Process

http://en.wikipedia.org/wiki/Support_Vector_Machines

xviii

K-NN K- Nearest Neighbor

MAX Maximum

MDD Missing Data Detector

MIN Minimum

NB Naïve Bayes

NCP Number of Correct Prediction

NOC Total Number of Cases

NOCR Number of Corrected Rules

NOP Total Number of Predictions

NOR Number of Rules

NWP Number of Wrong Predictions

RI Rule Induction

RS Rate of similarity.

ROC Receiver Operating Characteristic

SN Sensitivity

SNoW Sparse Network of Winnows

SP Specificity

SVD Singular Value Decomposition

SVM Support Vector Machines

TF/IDF Term Frequency –Inverse Documentation Frequency

TN True Negative

TNR True Negative Rate

TP True Positive

TPR True Positive Rate

xix

UML Unified Modeling Language.

VC Vapnik Chervonenkis

VSM Vector Space Model

WWW World Wide Web

xx

LIST OF SYMBOLS

C Corpus

CCR Correct Classification Rate

ER Error Rate

FN False Negative

FP False Positive

Hi Tested Hadith

I entropy Information entropy

IG Information Gain

J The total number of classes

K Attributes

L Dataset

M Feature

N Training instance/ sample size

NCP Number of Correct Prediction

NOC Total Number of cases

NOP Total Number of Predictions

NWP Number of wrong Predictions

P(i) Probability

Rcv

The V-fold cross validation accuracy

Rte

Validation accuracy

SP Specificity

TN True Negative

xxi

TNR True Negative Rate

TP True Positive

TPR True Positive Rate

V Subsets

v_best The best attribute

xi Instance

Yi Class

1

CHAPTER ONE

INTRODUCTION

1.1 THE IMPORTANCE OF HADITH

The Qur'an is the last divine book, which was revealed from Allah as a declaration

and guidance to mankind. It is an explanation of all things and means for men to be

rightly guided. In many verses of the Qur'an, it is commanded to obey the prophet of

Allah.

قُلْ أَطيعوا اللَّه وأَطيعوا الرسولَ فَإِنْ تولَّوا فَإِنما علَيه ما حملَ وعلَيكُم ما (بِينلاغُ الْمولِ إِلا الْبسلَى الرا عموا ودتهت وهيعطإِنْ تو ملْتمسورة () ح

)54النور Say: "Obey Allah and obey the Messenger, but if you turn away, he (Messenger Muhammad ) is only responsible for the duty placed on him (i.e. to convey Allah's Message) and you for that placed on you. If you obey him, you shall be on the right guidance. The Messenger's duty is only to convey (the message) in a clear way (i.e. to preach in a plain way)." (The Holy Qur'an 24: 54)1

This is quite a significant point because understanding the Qur'an fully can

only be possible with following the Sunnah of the prophet. Sunnah, means the actions,

sayings and silent permissions (or disapprovals) of the Prophet. The word Sunnah is

also used to refer to religious duties that are optional. Furthermore, Sunnah means the

recorded sayings (Hadith) of Prophet Muhammad . In this sense, Muslims believe

that the Sunnah of the Prophet Muhammad is the second of the two revealed

fundamental sources of Islam, after the Holy Qur'an (Hasan, 2004). It is impossible to

1 Translation of the meaning of the Nobel Qur'an was taken from http://www.dar ussalam.com/TheNobleQuran/ , The Nobel Qur'an.

2

understand the Qur'an without reference to the Hadith; and it is impossible to explain

Hadith without relating it to the Qur'an. Where the Quran gives Muslims a broad

framework for how they should live, the Hadith gives them specific information. For

instance:

Qur'an commands Muslim to pray, prophet Muhammad explained when and

how to pray:

)لُّوا كَملِّيصونِي أُصمتأَيا ر(َ .انخيالش هجرأَخ Perform your prayer in the same manner you had seen me doing [Reported by Al-Bukhai& Muslim].2

Qur'an commands Muslim to make Hajj, prophet Muhammad explained

how to perform Hajj

)اسني منذُوا عمٍ )كَكُمخلسم هجرأَخ Take from me your rituals (of Hajj) [Reported by Muslim]3

Moreover, Allah has informed in the surah Al-e Imran that the Prophet had

the characteristic of teaching the Qur'an and purifying mankind:

)ع اللَّه نم لَقَد هاتآي هِملَيلُو عتي فُسِهِمأَن نولاً مسر يهِمثَ فعإِذْ ب نِينمؤلَى الْم) ويزكِّيهِم ويعلِّمهم الْكتاب والْحكْمةَ وإِنْ كَانوا من قَبلُ لَفي ضلالٍ مبِينٍ

)164سورة آل عمران (Indeed Allah conferred a great favor on the believers when He sent among them a Messenger (Muhammad ) from among themselves, reciting unto them His Verses (the Qur'an), and purifying them (from sins by their following him), and instructing them (in) the Book (the Qur'an) and Al-Hikmah [the wisdom and the Sunnah of the Prophet (i.e. his legal ways, statements, acts of worship, etc.)], while before that they had been in manifest error (The Holy Qur'an 2: 164)

2Translation of the Hadith was taken from http://3refe.com/vb/showthread.php?t=160957 The official website of Dr.Al-Ereefi 3 Translation of the Hadith was taken from http://en.wathakker.net/articles/print/584 wathakker.com

3

It would be useful to attract attention to the phrase "teaching the book and the

wisdom which emphasizes the relationship between Qur'an and Hadith and indicates

Hadith as the second resource of the knowledge and wisdom, therefore, Hadith is an

important source of reference for the development of Islamic laws, the Muslim

community recorded prophet Muhammad's words and actions for posterity, and as the

number of these reported conversations grew exponentially in the century after his

death, the community developed sophisticated methods to evaluate their veracity to

know which traditions were reliable, and which were clearly fraudulent. While the

early collections of Hadith often contained Hadith that were of questionable origin,

collections of authenticated Hadith called Sahih (sound, true, correct) were compiled,

gradually by many Hadith scientists such as Al-Bukhari, Muslim, Al-Tirmidhi, Al-

Nasa'i, Ibnu Majah, Abu Daud, Al-Darimi, Malek and Ibnu Hanbal (Hadith-

traditional books, 2009).

1.2 BACKGROUND OF THE STUDY

Nowadays, many studies are published and much software are developed to serve the

prophetic tradition through several channels that can help students and scientists to

find tremendous amount of information in the simplest and the easiest way.

Furthermore, such software introduce quick electronic search instead of the manual

search (Aldhlan et al., 2010).

Most initial studies concentrated on transferring the Hadith resources books

such as Al-Bukhari collection, Muslim collection and other books into databases

either on websites or as software. However, it has become necessary to find smart

approaches that can adopt Hadith literature rather than simply storing Hadith

resources on a compact disk or websites with all probabilities of having negative

DATA MINING FOR HADITH CLASSIFICATION BY KAWTHER …

Documents

Transcript of DATA MINING FOR HADITH CLASSIFICATION BY KAWTHER …