IntelliBot: A Domain-specific Chatbot for the Insurance Industry MOHAMMAD NURUZZAMAN A thesis submitted in fulfilment of the requirements for the degree of Doctor of Philosophy UNSW Canberra at Australia Defence Force Academy (ADFA) School of Business 20 October 2020 ORIGINALITY STATEMENT ‘I hereby declare that this submission is my own work and to the best of my knowledge it contains no materials previously published or written by another person, or substantial proportions of material which have been accepted for the award of any other degree or diploma at UNSW or any other educational institute, except where due acknowledgement is made in the thesis. Any contribution made to the research by others, with whom I have worked at UNSW or elsewhere, is explicitly acknowledged in the thesis. I also declare that the intellectual content of this thesis is the product of my own work, except to the extent that assistance from others in the project’s design and conception or in style, presentation and linguistic expression is acknowledged.’ Signed Date To my beloved parents Acknowledgement Writing a thesis is a great process to review not only my academic work but also the journey I took as a PhD student. I have spent four lovely years at UNSW Canberra in the Australian Defence Force Academy (ADFA). Throughout my journey in graduate school, I have been fortunate to come across so many brilliant researchers and genuine friends. It is the people who I met shaped who I am today. This thesis would not have been possible without them. My gratitude goes out to all of them. Above all, I would express my supreme gratitude to my PhD supervisor, Assoc. Prof. Omar Khadeer Hussain, who has been a fantastic advisor throughout this journey. He has encouraged me to the challenging field of natural language processing and deep neural networks. He has been the most supportive of my work, providing me with excellent guidance and support in both academic and professional; and encouragement in times of need. In addition to this, he has also been very patient and understanding, more than anyone I have known. Prof Omar has made my journey an enjoyable one, provided lots of useful feedback, corrected my work extremely promptly, for which I have the utmost gratitude. He has also provided me with great opportunities to participate in a lot of interesting research projects. There would not exist this thesis without his constant support. Importantly, I would like to thank my parents Al-Hajj Sultan Ahammad and Sahana Sultana for their unconditional love throughout my life and provided me with the soil to grow. Without their support I may not have found myself at UNSW, nor had the courage to engage in this journey and see it through. My parents, to whom my academic career owes greatly and supported me wholeheartedly for my pursuit of dreams, even if that meant a distance of thousands of miles for many years. Furthermore, I thank to my younger brother Kamruzzaman Poran, two sisters Aspiya Sultana Shekha and Sultana Momotaz Sima, and two brothers-in-law Md Mahmud Reza and Salam Prodhan. I would not be at this stage I am today without their unflagging support and great sacrifices towards my education along the way. Words are not enough to express their encouragement and love in my life. Thank you very much for always being there for me. I am very grateful to have such a supportive family. I am also grateful to Assoc Prof Farookh Hussain and Dr Morteza Saberi, who always has confidence on me and encourages me to pursue a higher standard and for their generous help in addressing research issues and paper revision. I thank to Gianin Zogg for giving me valuable career advice and inspiration. To Samuel Sun and Ramesh Thiagalingam, who helped me solve the issues in the project and industry collaboration. Their insightful guidance and sense of responsibility motivate me towards professional personnel. To my colleagues Peter Scott and Greg Creighton for their supports on hypothesis explanation insightful technical conversations and participation in fruitful discussions. They have continuously demonstrated how to discover interesting problems, how to bake ideas and how to ruthlessly question a work, especially that of oneself. To my friends who aside from being teammates, Gautham Ravi and Yifan Zhao, whom I learned a lot while working with them. Thank you buddies, for your hard work and making our time worthwhile. And my deepest thanks to Saleh Ibne Rosul, Ashraf Chowdhury, his beloved wife Mahzabin Akhter and their little adorable daughter Ophelia Chowdhury, who makes it a big family to me and cares for me more than himself. Special appreciation goes to Farida Yesmin Shetu with whom I always share my good news and frustration. I couldn't complete this journey and achieve any accomplishment without their unconditional love. I would like to acknowledge the financial supports from UNSW, for providing international postgraduate award, tuition fees, research stipend and student health coverage. Life at UNSW Canberra at ADFA would have been much more difficult without members of the administrative and technical staffs. I would like to thanks to all staffs in the School of Business and School of Engineering and Information Technology at UNSW. I would like to take this opportunity to thanks my committee members Prof Michael O’Donnell, Prof Satish Chand, Dr Fiona Buick, Prof Elizabeth Chang, Jessica Campbell and Elvira Berra, for their extreme support and provided insightful comments to make this thesis deeper and more coherent. Special thanks to my UNSW friends Sukanto Kumer Shill, Abdul Khaleque, Hang Thanh Bui, Ahmad Jorban Al-mahasneh, Tasneem Rahman, Ahasanul Haque, Xiao Zhang, Md Alamgir Hossain, Tanmoy Das Gupta, Mohiuddin Khan, Sohel Ahmed, Anwar Us Saadat, Forhad Zaman, Mousa Hadipour, Wenxin Chen and Jo Ji. Also, I would like to thanks to all of my school friends Salahuddin Ahmed, Istiaque Ahmed, Saiful Islam, Mydul Hossain Khan, Kaniz Fatema, Mahbub Alam, Alauddin, Mohammad Razzakul Haider, Bashir Ahmed, Noor Mohammad, Mohammad Shazzad Hossain Bhuiyan, Isa Ahmmed Saleh, Shahin Ahmed, Golam Mostofa, Monower Hossen, Tanvir Hasan, Hedayet Ullah, Nazmul Islam, Shamim Hossain, Ruma Pervin, Zahid Hasan, Tahamina Alich, Shahana Akter Shelly, Ayesha Siddiqua, Mahmud Hasan, Nazmul Haque, Homayun Khan, Mohasin Ali, Mohammad Al Amin, Husne Ara, Asmaul Husna, Shamima Akter, Jesmine Akter, Rustom Ali, Shohidul Shazib, Nilima Ibrahim, Abu Ohab, Abbas Uddin, Rokonuzzaman, Azman Khan, Nasreen, Mahamuda, Bappi, Belal Hossain, Abu Bakar Siddique, Arifur Rahman and Sir Afzal Hossain, who left precious memories for me. I thank you for steering me to a better self. Last but not least, I thank to all my friends and family members specially SalBadiul Alam, Kamal, Abul Khair Mojumdar, Jahangir Alam, Mohammed Reaz, Al-Mamun, Alamgir Alam, Ahmad Abdul Majid, Walid Abouaghreb, Rajib Hasan, Aziz, Anawarul, Mahadi Miraz, Shamimul Azim, Taslima Akter Tasu, Faria Zaman, Nurjahan Akter Shanta, Michelle Williams, Nafis Iqbal, Zakir Hossain, Vinay Kumar Adepu, Fatin Nurul Ghazali, Sharmin Afroz, Tania Habib, Prof Hatim Mohammad Tahir, Prof Azham Hussain, Zhamri Che Ani, Mohammad Amir, Dr. Husbullah Omar, Prof Wan Rozaini Sheik Osman, Zaini Mostafa, Muhammad Aiman Mazlan, Dr Shifa Mahmod, Dr Azman Yasin, Peter Chong, Chang Fu Tong, Sing Choong Lau, Lee Teik Hui, Kevin Yap, Imam Hossain, Freed Jawad, Aumio Chowdhury, Akhlaqur Rahman, Ishrar Tabenda Hasan, Saeed Nezamy, Yogi Babria, Bahar Torkaman, Arif Yusof, Dina Rayhan, Ritesh Singh, Ajita Shah, Santosh Mainali, Sheikh Salam, Mesbahur Rahman Topu, Surya Maharjan, Ram Sharma, Reejo Augusti, Samir Khan, Tenzin, Baysaa Baatar, Farid Ahmed, Ang Ling Weay and Zannatul Mawa Dihan. I thank you for steering me to a better self. Abstract Communication is an indispensable aspect in the success of any business. Due to the increase in digital innovation, Internet-based services such as chatbots now play a vital role in maintaining communication between users. However, a traditional chatbot’s dialogue capability is quite inflexible as It can answer the user only if there is pattern-matching between the set of questions-answers and user’s query. This may leave the customers unhappy and research has shown that 91% of unhappy customers tend not to engage with the business again. To address this, chatbots needs to have meaningful dialogue abilities rather than merely providing either a yes, no or a short response. The major challenge in building a better AI model is ensuring it has a domain-specific conversational capability to engage with the user while presenting meaningful responses and semantically correct information. The existing literature has explored the capabilities of advanced techniques such as recurrent neural networks (DBRNN) for chatbots to engage in human-like conversation and generate responses. However, while an enormous amount of research has been done to bring this idea to realization, no significant outcome in the area of engaging with the users while generating a response is achieved to date. To address this problem, in this thesis, an innovative framework architecture, named IntelliBot, is designed and developed. IntelliBot is a chatbot which to facilitate a high degree of engagement with the user using the seq2seq model when generating its response with the user. Additionally, it not only has the ability to answer a question, but also complex user queries with a semantically correct meaningful response and solves user queries specifically in the insurance domain. To meet these challenges, IntelliBot generates a response in four distinct ways, namely, template-based strategy, knowledge- based strategy, internet retrieval strategy and generative-based strategy. An AI selection process is adopted which sequentially determines which strategy fits best according to the specifics of the user’s question. To demonstrate the effectiveness of IntelliBot in generating a superior response, its outputs are evaluated against three publicly available chatbots.