Developing Chatbots

Manaswi, Navin Kumar

doi:10.1007/978-1-4842-3516-4_11

Cited by 4 publications

(4 citation statements)

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“…Chatbots rely on a variety of frameworks that govern their operations. For example, chatbots developed by Microsoft differ from those developed by Facebook (Manaswi, 2018 ). Although they both have the same purpose of receiving instant messages, they differ in the programming languages used in their development, the type of conversations they provide to the user, and the data models stored in their databases (Hwang and Chang, 2021 ).…”

Section: Literature Reviewmentioning

confidence: 99%

“…In this manner, appropriate responses are presented to the user considering the intent of the conversation and contextual information (Hwang and Chang, 2021 ). Studies have shown that chatbots have three types of appropriate response generation models: pattern-based, retrieval-based, and generative models (Manaswi, 2018 ). The pattern-based model generates appropriate responses depending on the exact match between the question and the answer stored in the database.…”

Section: Literature Reviewmentioning

confidence: 99%

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Implementing the Bashayer chatbot in Saudi higher education: measuring the influence on students' motivation and learning strategies

2023

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Since the fourth industrial revolution, intelligent software and applications that attempt to mimic human behavior have become increasingly common. The chatbot is an example of an artificial intelligence-based computer program that simulates human behavior by having a conversation and interacting with users using natural language. The implementation of chatbot technology in the educational context is still in its nascent stage, and further investigation into measuring its effectiveness in supporting learning and teaching processes is required, particularly in the context of higher education. Thus, this study presents the design and implementation of a task-oriented chatbot, that is embedded into the WhatsApp application, called Bashayer. It aims at supporting postgraduate students' motivation and learning strategies in Saudi Arabia. A quasi-experimental design with a single-subject experimental approach was adopted with a sample of 60 Saudi postgraduate students. The descriptive analysis of the collected data showed promising results of postgraduate students utilized the Bashayer chatbot system. Participants in the experimental group that used Bashayer were more motivated to learn than those in the control group. Participants also practiced more cognitive and metacognitive learning strategies while utilizing the chatbot compared to the control group. The results of this study are encouraging for the development of chatbot systems similar to Bashayer to support postgraduate students' successful learning. These results contribute to bridging the research gap and adding to the literature on chatbots use in postgraduate educational contexts.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Implementing the Bashayer chatbot in Saudi higher education: measuring the influence on students' motivation and learning strategies

2023

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“…Manaswi, N.K. [15] proposed steps for Building a Chatbot which involves Word2Vec, Tokenization, Removing Punctuation Marks, Removing Stop Words, Term Frequency-Inverse Document Frequency (TF-IDF), Named Entity Recognition using NLTK and Intent Classification, Word Embedding, etc techniques which form basis of many NLP and neural network based chatbots. Mittal M Et al [16] successfully developed chatbot using Gradient Descent Algorithm and Natural language processing techniques such as tokenisation, stemming and enumeration to make bag of words.…”

Section: Vmentioning

confidence: 99%

Neural Network and Natural Language Processing Based Anti-Depression Chatbot

Atram,

Chitalkar,

Ali

et al. 2023

IJRASET

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More than one in eight teenagers suffer from mental health issues like depression which is now becoming a common thing in society nowadays which can more often lead people to take extreme steps like suicides. Anti-Depression Chatbot is ideal, cost-effective, highly available web based Chatbot to help fight depression. Users can trust and turn to Anti-Depression Chatbot by simply using any browser for seeking help if they are feeling depressed. When user chats with Anti-Depression Chatbot about depression, mental health and things causing depression like toxic relationships, etc bot replies to user positively and provides information, advises user, etc in such a way that users depression level or sadness reduces. Anti-Depression Chatbot uses Natural Language Processing to understand user and replies with limited amount knowledge it has, to successfully reduce depression and boost mental health of user.

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“…Tess [9] tries to imitate humans to act as partner with whom we can share our feelings uses various therapy techniques, gives personalised solutions and is based on decade of research work. Chatbots can be built using various natural language processing techniques like Term Frequency-Inverse Document Frequency (TF-IDF), Word2Vec, Stemming, Removing Punctuation Marks and Stop words, Tokenization, Intent Classification, Word Embedding, etc [10].…”

Section: Literature Surveymentioning

confidence: 99%

Design and Implementation of Feed Forward Neural Network Based Chatbot for Depression Support

Atram

2023

IJRASET

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As the awareness related to mental health is increasing, there is a need to make the assistance related to it more accessible. According to recent studies, people avoid in person counselling when it comes to mental health. Hence alternatives need to be made available to help people to live a stress-free life. We proposed this system in hope to address this topic in form of a chat-bot which engages users to have a positive conversation. This will surely reduce the loneliness and stress which people might find difficult to share with other people. This chatbot is built using feed forward neural network to generate appropriate response.

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Developing Chatbots

Cited by 4 publications

References 0 publications

Implementing the Bashayer chatbot in Saudi higher education: measuring the influence on students' motivation and learning strategies

Implementing the Bashayer chatbot in Saudi higher education: measuring the influence on students' motivation and learning strategies

Neural Network and Natural Language Processing Based Anti-Depression Chatbot

Design and Implementation of Feed Forward Neural Network Based Chatbot for Depression Support

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