Enhanced Admission Enquiries System Using Chatbot Technology

2.2 Chabot Technology and Human Deception 6

2.3  The Imitation Game

2.4  Some Early Systems

          2.4.1  ELIZA

1. 2.4.2  PARRY

2. 2.4.3  A.L.I.C.E

3. 2.4.4  VPbot 

   2.4.5 Eugene Goostman 13

   2.4.6  Artificially Intelligent Conversational Agents in Libraries 14

   2.4.7  An Intelligent Internet Shop-Assistant 14

   2.4.8  Dialogue-based CALL: a case study on teaching pronouns 15

   2.4.9  Motivate Learners to Practice English through Playing with Chatbot CSIEC 16

   2.4.10  Dialogue Based Assistant for Career Counseling 16

   2.4.11  Interactive System with Artificial Intelligence 16

   2.4.12  Designing a Chatbot for Diabetic Patients 16

   2.4.13  Chatbot for admissions 17

   2.4.14  Bringing Chatbots into Education 

   2.5 Elements of AIML 19

   2.5.1  Categories 

   2.5.2  Types of ALICE/AIML Categories 20

   2.6  Learning Chatbots 22

   2.7  Interaction with humans 23

   2.8  Summary of Related works 

   CHAPTER THREE: METHODOLOGY AND SYSTEM ANALYSIS

   3.1 Methodology
   3.1.1 Justification for the Choice of Methodology 

   3.2 Analysis of the Existing Systems

   3.2.1 Existing Approach to Admission Enquiries in FUTO 

   3.2.2 Problems in the Existing approach 

   3.3 Analysis of the Existing System

   3.3.1 Weaknesses of the Existing System

   3.4 Analyses of the Proposed System

   3.5 Web Applications 

   3.6 Functional Requirements

   3.7 Non-Functional Requirements 

   3.8 Justification for the Proposed System

   CHAPTER FOUR: SYSTEM DESIGN AND IMPLEMENTATION

   4.1 Design Objectives

   4.2 Design Specification

   4.3 Database Design 

   4.4 Keyword Matching Algorithm

   4.5 Framework of the Proposed System

   4.6 System Flow Chat 

   4.7 Choice and Justification of Programming Language Used

   4.7.1 Database Server

   4.7.2 Web Servers

   4.7.3 HTML and CSS

   4.7.4 Third Party Libraries (Program - O)

   4.8 Implementation
   4.8.1 Programming Tools
   4.9. System Requirements

   4.9.1 Hardware Requirements
   4.9.2 Software Requirements

   4.10 Testing and Evaluation
   4.11 Result Analysis

   4.11.1 Result Analysis Based on Perceived Usefulness
   4.11.2 Analysis of the Result Based on Perceived Ease of Use

   4.12 Documentation

   CHAPTER FIVE: SUMMARY AND CONCLUSION

   1. 5.1  Summary

   2. 5.2  Problems Encountered and Solution 67

   3. 5.3  Contribution to Knowledge 67

   4. 5.4  Conclusion 68

   5. 5.5  Recommendations for Future Work: 69

   References

   APPENDIX A SOURCE CODES

   APPENDIX B SCREENSHOTS OF THE SYSTEM

   1. B1  Admin Login Page 

   2. B2  User Interface 

   3. B3  Sample Conversation with the Chatbot 

   4. B4  Rating the Chatbot in Terms of Perceived Usefulness and Ease of Use 

   1. B5  Results of rating

   2. B6  List of Sample Text

    LIST OF FIGURES

   Figure 2.1: Figure 2.2: Figure 2.3: Figure 2.4: Figure 3.1: Figure 3.2 Figure 3.3: Figure 3.4: Figure 4.1: Figure 4.2 Figure 4.3: Figure 4.4: Figure 4.5: Figure 4.6: Figure 4.7: Figure 4.8: Figure 4.9: Figure 4.10: Figure 4.11: Figure 4.12: Figure 4.13: Figure 4.14: Figure 4.15: Figure 4.16:

   LIST OF FIGURES

   Turing test involving a judge interrogating two hidden entities 9

   A sample conversation with ELIZA 10

   A sample conversation with ALICE 13

   A sample conversation with Eugene 14

   waterfall Methodology 28

   Architecture of the Existing System 31

   A Detailed Architecture of the Proposed System 32

   Three Tier Architecture 33

   Entity Relationship Diagram 37

   the Difference between Search Engine and Matrix Engine 39

   The Importance of Matrix Engine 39

   High Level Design. 42

   System Flow Chat 43

   Back End User Interface 55

   Graph of Perceive usefulness for group 1 56

   Graph of Perceived ease of use for group 1. 57

   Graph of Perceive usefulness for group 2 58

   Graph of Perceived ease-of-use for group 2. 58

   t distribution plot of PU25 and PU30 MEANS 61

   t distribution plot of PEU25 AND PEU30 MEANS 63

   Admin Login Page. 64

   User Interface 65

   Rating the System. 65

   Results of Rating from Different Participants 66 

   LIST OF TABLES

   Table 2.1:

   Table 4.1: Table 4.2:

   Table 4.3 Table 4.4: Table 4.5: Table 4.6:

   LIST OF TABLES

   List of Some Existing Chatbot 24

   Input Specification 35

   output Specification 36

   Database Structure 36

   keyword matching 41

   Rating Result For group 1(users with maximum age of 25)

   57 Rating result for group 2(users with minimum age of 30)