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A Survey on Various Types of Chatbots
1.
International Research Journal
of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 09 Issue: 07 | July 2022 www.irjet.net p-ISSN: 2395-0072 © 2022, IRJET | Impact Factor value: 7.529 | ISO 9001:2008 Certified Journal | Page 688 A Survey on Various Types of Chatbots Supreetha H V1 1M. Tech Student, Dept. Of CS&E, RVCE Bengaluru, Karnataka, India ---------------------------------------------------------------------***--------------------------------------------------------------------- Abstract - Chatbots are software applications which are mainly used to perform tasks asked by the users. Thesearejust like virtual assistants. With the increase in conversational medias, chatbot’s application increased drastically. Many social media, e-commerce, banking sectors also use these chatbots for easy access to the customers. These chabtots can communicate with users anytime and they won’trequiremore cost for maintenance. Thus many websites andconversational platforms are choosing chatbots as face of their products. The aim of this paper is to get to know in-details about various kinds of chatbots available in market and their applications in real life scenarios. Key Words: chatbots, conversational media, ML, NLP, virtual assistants 1.INTRODUCTION Machine learning and artificial intelligence are hot topics in recent times. The growth in these domains have made huge impact in many ares. One of the major applications of these domains can be seen in chatbots. The chatbots just try to imitate human behaviour and tries to help users. The increase in chatbot can decrease work load of many industries. Say in an e-commerce website, the chatbot can interact with user and learn user’s personal interests and suggest some of the product. This will make customerhappy and will also help sellers to increase their profit. Some of the chatbots can also be used in health field also to boost the confidence of the users. Say if a person is in depression and is not ready to share his difficulties with family and friends, he can converse with chatbot to come out from the state of mind. Similarly chatbot’s application can be seen in many areas. 1.1 Natural Language Processing NLP is the reason which caused the developmentofchatbots. With natural language understanding, thechatbotswilltryto understand the context of the user given input and provide suitable responses forthe users. The NLU can be dividedinto further stages namely, lexical analysis, syntax analysis, semantic analysis, disclosureintegration,pragmaticanalysis. Lexical analysis include splitting of user given inputs to paragraphs, sentencesandwords.Thesyntaxanalysischecks for logical meaning of the user given inputs. Checks if all words are correctly placed in order or not. “The good is flower” is rejected by English syntactic analyzer. The sentence is not placed in meaningful way hence it will be rejected. It will take care of grammatical part. The semantic analysis will try to understand context and tries to understand if there is any meaning for users sentence. Say if a user asks if the milk is black? The bot should reject such logic-less questions as it don’t have any meaning. Disclosure integration stage makeschatbotmoreconversationalenough for users. This will track the progress of chat and tries to link current and previousstates to providemeaningfulresponses for users. The pragmatic analysis do real time analysis for understanding queriesaskedby theusers.Thediagrammatic representation of stages in NLU is given in Figure 1. Figure 1. Stages in NLU The organization of the report is as follows the section 2 will discuss about the various kinds of chatbots and its applications and section 3 will give conclusion followed by reference section. 2. TYPES OF CHATBOTS Chatbots can be broadly classified into two types, they are: AI chatbots and Rule based chatbots. AI chatbots are recent developments which are using intelligent systems for giving outputs to uses. It requires more training for these chatbots to behave like humans. Some times these bots are trained in such away that it would become much difficult even for users to understand whether a other end if it is user or a bot they are conversing with. Rule based bots don’t require much training, they will be having set of questions and answers they can interact only for those set of queries.
2.
International Research Journal
of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 09 Issue: 07 | July 2022 www.irjet.net p-ISSN: 2395-0072 © 2022, IRJET | Impact Factor value: 7.529 | ISO 9001:2008 Certified Journal | Page 689 This section gives indetaileddescriptionaboutvariouskinds of chatbots with its applications. Menu based chatbots, Linguistic chatbots, ML chatbots, Hybrid chatbots, keyword recognition chatbots and Voice bots. Thediagrammaticview of this is shown in Figure 2. 2.1 Menu Based Chatbots These chatbots are initially trained with yes or no option menus. The next question asked by the bot will be linked with the answer given in the present stage. These bots will be pre-fed with list of questionnaires with its answer path for two options also. The answer chosen by user will determine next set of questions. Mainlydecisiontreemodels are used to train this type of chatbots. Figure 2. Types of chatbots 2.2 Linguistic Chatbots Many linguistic chatbots can be seen now-a-days. A wide range of applications are based on this type of chatbots. Many social media platforms like facebook, messenger will be having a number of linguistic chatbots. These bots will attract large audience because many users will not beaware of English language. Adding linguistic chatbots will attract more customers for a given website and finally increasing the profit of the organizations. Many times these bots are created for language learning and language translation purpose also. These will help to learn new languages by giving translations in user asked languages. In a placewhere we don’t know native language, I would be beneficiary 2.3 ML chatbots The ML chatbots will be properly trained bots. These will be trained for intent entity selection and response giving methodologies. Many platforms will provide open source tools to develop these chatbots. Some of the very famous platforms where one can develop these kindsofchatbotsare DiaglogFlow, RASA, gupshup interface, BotKit etc.These will be having template for chatbot development where one can create bots according to their needs. They also provide integration with other messaging platforms like whatsapp, facebook, telegram etc to deploy build chatbots. One can select any ML models of their interest to develop chatbots here. Some of the models that can be used are RNN, Neural network modes, DIET classifiers, CNN models etc.According to users comfort they can choose any model to train the chatbots. 2.4 Voice Bots The main advantage and growth of chatbot was seen once voice based chatbot were developed. Because large number of audience don’t wish to type or some people don’t know how to type. With the voice bots, all these challenges are solved. This chatbot will be having an additional feature of text-to speech or speech-to-textconversions.ManyAPI’swill help to enable this feature. The main usecase of this chatbots can be found for specially visualized persons also. They can give input to the bots by voice and the chatbot will respond back with voice outputs. Thus they can b used even as assistants by specially visualized persons. Some of the additional functionalitieslikesending e-mail,voicemessages can also be possible using these bots. 2.5 Keyword Recognition based Chatbots These are requirement specific chatbots. Say if a user asks “book a movie ticket”, the chatbot will try to retrieve keywords such as book and movie ticket. It will first collect the keywords from the queries and then process it. If a bot can’t understand the keyword then proper output can’t be given and sudden stop or no response from the bot could be observed. Hence in these cases proper training of chatbots are very much essential. More the training lesser will be non reorganization of keywords. 2.6 Hybrid Model Chatbots These bots will be having both features of menu drive chatbots and AI enabled chatbots. These are growing chatbots now-a-days. In real time scenarios may people will be lazy enough to type and answer all the queries asked by the users, So if in another flow, a set of questions with list of options are provided, users can switch the wayofanswering according to their convenience. Many of the well developed e-commerce websites will use this hybrid bots for their websites. They will provide set of products as menu driven and sometimes they will also converse contextually with users to engage them more with their products. Hence this bot is a milestone in chatbot history. Table 1 will give comparison of types of chatbots.
3.
International Research Journal
of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 09 Issue: 07 | July 2022 www.irjet.net p-ISSN: 2395-0072 © 2022, IRJET | Impact Factor value: 7.529 | ISO 9001:2008 Certified Journal | Page 690 Table 1 Comparison of types of chatbots Chatbot AI/ Rule Based? Time for Response giving and Training Advantages Limitations Menu Based Chatbots Rule Based Less Training. Less Response time. Quickly response will be obtained. Less ambiguity as paths are pre defined. Limited usage. Only used for Yes/No type of questions. Linguistic Chatbots AI Based More Training. More Response time. Helpful for language learning. Can be integrated with multiple messaging platforms More training is required. Sometimes more training may lead to overfitting. ML Chatbots AI Based More Training More Response Time Conversational bots just like humans. Context preserved. More training is needed to get accurate results. As it needs processing response time is also more user needs to wait to get response. Voice Bots AI Based More Training More Response Time Helpful for specially visualized group. No typing is required. Extra step of text-to-speech or speech-to- text. Difficult to understand the accent of users correctly. Keyword Recognition Based Chatbots Rule Based More Training More Response Time Easy for pre-trained data Fast response. More training. Limited set of queries can be answered. Hybrid Chatbots AI & Rule Based More Training More Response Time Interactive Gives personalized outputs Much time for training. Complex architecture. 3. APPLICATIONS OF CHATBOTS The applications of chatbots can be seen in manyareas.Some of the area of applications of chatbots are discussed in this section. The diagrammatic representation of chatbot’s application is shown in Figure 3. 3.1 CUSTOMER SUPPORT Whenever a user is having any issues or doubts he usually calls to toll free numbers of customer care. They need to wait for long period to get their turn. It would be tedious even for users and also forth person who needs to answer these calls.
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International Research Journal
of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 09 Issue: 07 | July 2022 www.irjet.net p-ISSN: 2395-0072 © 2022, IRJET | Impact Factor value: 7.529 | ISO 9001:2008 Certified Journal | Page 691 If a chatbot is given training for answering these questions it would be easier. Much of time is not wasted on repetitive tasks. Moreover chatbots wont get tired and they can be made available 24/7 with less maintenance cost. 3.2 SOCIAL MEDIA These bots will be incorporated in social media for engaging people. Sometimes the chatbots can be harmful also in some social media platforms. Say in Instagram people may create fake bots to increase popularity of a person. They may fake like and comment usingchatbots.Similarcaseswerefoundin Twitter also where people will buy bots to change the mindset of people. Some chatbots are also used in creating fake profiles just to give fake follower numbers for users in many social media platforms. Figure 3. Applications of chatbots 3.3 TRAVEL AENCIES Many travel agencies use chatbots in their websites. These bots will help in finding customized hotels, restaurants also. The bots will take care of finding the tickets in different modes like planes, trains andalso help to get bookingingood hotels and restaurants. This will make bookings easy for users and increase the profits of the agencies. 3.4 ASSITANT TO PERSONS The bots can also be used as personal assistants. Some of the famous personal assistants are Siri, Alexa, google’s assistant. These can be used forentertainment purpose also. Theyhelp to engage users by giving some activities or recommending some personalized music, comedies, news etc. They can also be used to track the day-to-dayactivitiesofusersandcanalso be used to get alert reminders. 3.5 SKILL ENHANCEMENT Many chatbots will help in skill enhancements by giving personalized recommendation systems for users’ interest. They will collect users interests and give more training regarding skills such as poster making, digital drawings and video editing and makings. 3.6 BANKING SECTORS In recent days all banking sectors have moved to online platforms. With this advancement they have also included chatbots in their website to guide users of all the benefits they offer. The bots willalso suggestthetypeofaccountusers can open, the interests in different accounts,interestsoffered by the bank and loan facilities. It will help users as they need not wait in long queues inside bank to get all the details. In online only users can understand all the facilities of banking sectors. It will reduce time of users also and reduce burden on bank employees. 4. CHALLENGES OF CHATBOTS There are some challenges wile implementing of the chatbots. Some of them are: 4.1 SECURITY AI chatbots needs to collect information and data which are needed to transmit over Internet. The bots must make sure that the confidential information about the users are not shared with anyone and help to maintain privacy of users. 4.2 UNDERSTANDING EMOTIONS There may be cases where user my give abbreviations as inputs, and sometimes bot needs to consider redundant words, and negative words to understand exact context of the request asked by the users. Proper training of chatbot is needed to overcome these challenges. 5. CONCLUSIONS With growth in technology many of the platforms have included chatbots insidetheirapplications.Alargenumberof chatbots are already developed in health, e-commerce,social media, customer service and educational sectors. The main aim of this paper is to understand various types of chatbots and the areas in which theycanbeusedfor.Fromtheanalysis it could be seen that almost every field is incorporating chatbots based on their requirements. Thus in coming days once can see major increase in number of chatbots and its applications, One need to understandbothitsdrawbacksand applications and try to use this chatbot as in favour to help others.
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International Research Journal
of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 09 Issue: 07 | July 2022 www.irjet.net p-ISSN: 2395-0072 © 2022, IRJET | Impact Factor value: 7.529 | ISO 9001:2008 Certified Journal | Page 692 REFERENCES [1] M. M. Khan, "Development of An e-commerce Sales Chatbot," 2020 IEEE 17th International Conference on Smart Communities:ImprovingQualityofLifeUsingICT, IoT and AI (HONET), 2020, pp. 173-176, doi: 10.1109/HONET50430.2020.9322667. [2] S. Thorpe and H. Scarlett, "Towards a Cyber Aware Chatbot Service,"2021IEEEInternational Conferenceon Big Data (Big Data), 2021, pp. 6040-6042, doi: 10.1109/BigData52589.2021.9671775. [3] W. Mahanan, J. Thanyaphongphat, S. Sawadsitang and S. Sangamuang, "College Agent: The Machine Learning Chatbot for College Tasks," 2022 Joint International Conference on Digital Arts, Media and Technology with ECTI Northern Section Conference on Electrical, Electronics, Computer and Telecommunications Engineering (ECTI DAMT & NCON), 2022, pp. 329-332, doi: 10.1109/ECTIDAMTNCON53731.2022.9720420. [4] P. Srivastava and N. Singh, "Automatized Medical Chatbot (Medibot)," 2020 International Conference on Power Electronics & IoT Applications in Renewable Energy and its Control (PARC), 2020, pp. 351-354, doi: 10.1109/PARC49193.2020.236624. [5] N. Kanodia, K. Ahmed and Y. Miao, "Question Answering Model Based Conversational Chatbot using BERTModel and Google Dialogflow," 2021 31st International Telecommunication Networks and Applications Conference (ITNAC), 2021, pp. 19-22, doi: 10.1109/ITNAC53136.2021.9652153. [6] J. Doshi, "Chatbot User Interface for Customer Relationship Management using NLP models," 2021 International Conference on Artificial Intelligence and Machine Vision (AIMV), 2021, pp. 1-4, doi: 10.1109/AIMV53313.2021.9670914. [7] P. Voege and A. Ouda, "A Study on Natural Language Chatbot-based Authentication Systems," 2021 International Symposium on Networks, Computers and Communications (ISNCC), 2021, pp. 1-4, doi: 10.1109/ISNCC52172.2021.9615767. [8] R. Garg et al., "NLP Based Chatbot for Multiple Restaurants," 2021 10th International Conference on System Modeling & Advancement in Research Trends (SMART), 2021, pp. 439-443, doi: 10.1109/SMART52563.2021.9676218. [9] D. P. P. Villanueva and I. Aguilar-Alonso, "A Chatbot as a Support SystemforEducational Institutions," 202162nd International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS), 2021, pp. 1-6, doi: 10.1109/ITMS52826.2021.9615271. [10] H. Beattie, L. Watkins, W. H. Robinson, A. Rubin and S. Watkins, "Measuring and Mitigating Bias in AI- Chatbots," 2022 IEEE International Conference on Assured Autonomy (ICAA), 2022, pp. 117-123, doi: 10.1109/ICAA52185.2022.00023. [11] C. J. Luo and D. E. Gonda, "Code Free Bot: An easy way to jumpstart your chatbot!," 2019 IEEE International Conference on Engineering, Technology and Education (TALE), 2019, pp. 1-3, doi: 10.1109/TALE48000.2019.9226016. [12] S. Meshram, N. Naik, M. VR, T. More and S. Kharche, "Conversational AI: Chatbots," 2021 International Conference on Intelligent Technologies (CONIT), 2021, pp. 1-6, doi: 10.1109/CONIT51480.2021.9498508.
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