Chatbot Datascience Proposal, Schemes and Mind Maps of Computer Science

Download Chatbot Datascience Proposal and more Schemes and Mind Maps Computer Science in PDF only on Docsity!

Section 1: Student Details

Full name:

Student number:

Award / course: BSc Computer Science

Email address:

Supervisor:

Date of submission: 31/12/

Table of Contents

• SECTION 1: STUDENT DETAILS.
• TABLE OF CONTENTS.
• SECTION 2 STATEMENT OF PROJECT.
• 2.1 PROJECT TITLE
• 2.2 ACADEMIC QUESTION.
• 2.3 UNIVERSITY ENQUIRY CHATBOT (PROPOSED) TO BE DEVELOPED.
• SECTION : 3 PROJECT PROPOSAL.
• 3.1 INTRODUCTION.
• 3.2 INITIAL RESEACH INTO SOURCES OF INFORMATION.
• 3.3 UNIVERSITY CHATBOT (proposed).
• 3.4 REFERENCES.
• SECTION : 4 ADDITONAL SOURCES OF INFORMATION.
• 4.1 RESOURCES.

Section 3: Project Proposal 3.1 Introduction This project is focusing on creating a chatbot to be used by students to get their queries responded easily from the college website. A chatbot is a program which can do real conversations with textual and/or auditory methods. Using Artificial Intelligence (AI), chatbots can simulate human conversations. There are two categories of chatbots. One category is command based chatbots where chatbots rely on a databank of replies and heuristics. The user must be very specific while asking the questions so that the bot can answer. Hence, these bots can answer limited set of questions and cannot perform function outside of the code. The other category is chatbots based on AI or machine learning algorithms, these bots can answer ambiguous questions which means the user do not have to be specific while asking questions. Thus, these bots create replies for the user’s queries using Natural Language Processing (NLP). Figure : 1 show that How a Chatbot works Figure 1 shows how a chatbot works. Whenever a user asks any query, the bot will first investigate the application, then finds intents and units, builds an answer and sends it back to the user. Now, intents mean intention of the query and entity means details of that query. For example, if a student wants to know the office hours of a faculty then the intent will be office hours and entity will be name of the faculty in this case.

AI-powered chatbots are motivated by the need of traditional websites to provide a chat facility where a bot is required to be able to chat with user and solve queries. When live agent can handle only two to three operations at a time, chatbots can operate without an upper limit which really scales up the operations. Also, if any school or business is receiving lots of queries, having a chatbot on a website takes off the load from support team. Having a chatbot clearly improves the response rate compared to human support team. In addition, since millennials prefer live chats over a phone call, they find a chatbot, which provide a highly interactive marketing platform, very attractive. Furthermore, a chatbot can automate the repetitive tasks. There can be some scenarios where a business or school receives same queries in a day for many times and support team must respond to each query repetitively. Lastly, the most important advantage of having a chatbot is that it is available 24/7. No matter what time it is, a user can get a query solved. All these advantages of a chatbot constitute the motivation to implement a University Enquiry Chatbot

3.2 Initial Research into source of Information

In order to understand the requirement of a chatbot, consider an example of Amazon Shopping App. In this app, when a customer buys an item, he/she does not have any information about how to return the item. To get this information, the customer must call and wait to talk to customer representative for a long time. However, this whole process is tedious for a customer. Hence, Amazon created a chatbot to answer simple queries of customers. Similarly, the university Enquiry Chatbot is designed to help students to get their queries solved on a fingertip. The study proposes that “there is a need to understand and consider the stability, scalability, and flexibility issues along with high level of intention of a human language”. Hence, for implementing a chatbot that handles complicated queries, the sentiment analysis is incorporated into University Enquiry Chatbot. Sentiment analysis aims to obtain writer’s feelings expressed in positive, negative or neutral comments. Based on sentiment analysis, the bot is trained to have empathy while answering to the user. For example, if a user says, “I am sad today.” then bot should reply to it with some empathy like “I’m sorry to hear that, how can I help you today?” and not just reply the standard message like “Sorry did not understand your question.” Another downside which was found during a research on

Microsoft Azure

Microsoft Azure provides cloud services to build, manage, and deploy applications on a cloud network which helps organization to meet their business needs using their favourite tools and frameworks. College Enquiry Chatbot uses all the services shown in Figure 2 which are provided by Microsoft Azure. Azure Bot Service Azure bot service is a service provided by Microsoft Azure which builds and artificial intelligence (AI) chatbot. It offers the ability to add intelligent agents that can do conversations with users without having to commit the resources to develop one’s own AI.

Azure Web App

I have used Azure web app to host my bot application build by Azure bot service. Azure Web App are the web applications which are hosted on Microsoft Azure cloud without any programming language barrier. Since it is hosted on the cloud, infrastructure maintenance is not needed to host the applications. It also provides various features like auto scaling, automated deployment and supports both Windows and Linux environments.

Azure Cognitive Services

Azure Cognitive services are used to add intelligence to the bots by adding features such as sentiment analysis and language understanding which help in analysing user's queries. These services can be added to an existing bot by adding service calls to the Microsoft's SDK to get the desired results. College Enquiry Chatbot utilizes Text Analytics, LUIS, and QnA Maker services which are part of cognitive services and use natural language processing (NLP) for different purposes.

Sentiment Analysis

Figures 3 and 4 show how a bot is answering the irrelevant questions of a user for which normal bots are not showing any kind of empathy. To make the bot to be able to respond these kinds of responses, the bot is trained with the chitchat integration which is provided by QnA Maker in which there are lots of questions and answers pairs are available.

Figure :3 Friendly Conversation Figure : 4 Friendly Conversation

3.4 References:

[1] "Chatbot", en.wikipedia.org, 2010. [Online]. Available: https://en.wikipedia.org/wiki/Chatbot. [Accessed Jul. 10, 2018]. [2] "Chatbot: What is Chatbot? Why are Chatbots Important? -", Expertsystem.com, 2018. [Online]. Available: https://www.expertsystem.com/chatbot/. [Accessed Sep. 11, 2018]. [3] "Amazon.com: Online Shopping for Electronics, Apparel, Computers, Books, DVDs & more", Amazon.com, 2017. [Online]. Available: https://www.amazon.com/. [Accessed Sep. 12, 2018]. [4] "Amazon Alexa - Build for Amazon Echo Devices", Developer.amazon.com, 2017. [Online]. Available: https://developer.amazon.com/alexa. [Accessed Sep. 12, 2018]. [5] "Meet Erica, Your Financial Digital Assistant From Bank of America", Bank of America,

2018. [Online]. Available: https://promo.bankofamerica.com/erica/. [Accessed Sep. 12, 2018]. [6] C. Doug Gross, "Facebook: Get Messenger app or else - CNN", CNN, 2014. [Online]. Available: https://www.cnn.com/2014/07/29/tech/socialmedia/facebook-messenger/ index.html. [Accessed Sep. 12, 2018]. [7] A. Storman, "5 Chatbot Challenges and How to Overcome Them", Chatbots Magazine,
2019. [Online]. Available: https://chatbotsmagazine.com/5-chatbotchallenges-and-how-to- overcome-them-caccc3a26d7c. [Accessed Sep. 11, 2018]. [8] A. M. Rahman, A. A. Mamun and A. Islam, "Programming challenges of chatbot: Current and future prospective," in 2017 IEEE Region 10 Humanitarian Technology Conference (R10- HTC), Dhaka, 2017. [9] "Problems with Chatbots Today - Attunix", Attunix, 2018. [Online]. Available:

https://attunix.com/problems-chatbots-today/. [Accessed Sep. 11, 2018]. [10] "Azure Bot Service - chatbot | Microsoft Azure", Azure.microsoft.com, 2017. [Online]. Available: https://azure.microsoft.com/en-us/services/bot-service/. [Accessed Jul. 22, 2019]. [11] "LUIS (Language Understanding) – Cognitive Services – Microsoft Azure", Luis.ai, 2017. [Online]. Available: https://www.luis.ai/home. [Accessed Jul. 15, 2018]. [12] "QnA Maker", Qnamaker.ai, 2016. [Online]. Available: https://www.qnamaker.ai/. [Accessed Jul. 17, 2018]. [13] "What is Azure Bot Service? - Definition from WhatIs.com", WhatIs.com, 2018. [Online]. Available: https://whatis.techtarget.com/definition/Azure-Bot-Service. [Accessed Jan. 17, 2019]. [14] "Azure App Service Documentation - Tutorials, API Reference", Docs.microsoft.com,

2015. [Online]. Available: https://docs.microsoft.com/enus/azure/app-service/. [Accessed Dec. 17, 2018]. [15] "Cognitive Services | Microsoft Azure", Azure.microsoft.com, 2017. [Online]. Available: https://azure.microsoft.com/en-us/services/cognitive-services/. [Accessed Dec. 22, 2018].