power on automation artificial intelligence - chatbot · artificial intelligence chatbot is a...

POWER ON AUTOMATION ARTIFICIAL INTELLIGENCE -

CHATBOT

Kalyani.Priyanka1, R.ElizabethAbishikta2,V.Greeshma3,Mr C kishor Kumar Reddy4 ,

Dr.B V RamanaMurthy5 .

Stanley College Of Engineering And Technology For Women ,Hyderabad--500001.

[email protected] , [email protected], [email protected],

[email protected], [email protected].

Abstract

Artificial intelligence chatbot is a technology that makes interaction between man and machines

in their natural language. Starting in 1966 with the interaction of ELIZA chatbot a great deal of

effort has been towards the goal of developing chatbot system . The main goal of the chatbot

VI’s to make a conversation between students and machine. The chatbot consists of core and

interface .the knowledge of the chatbot is stored in the form of ATML (artificial intelligence

markup language)programs. A human users can ask to the system like they usually do to

another human. This applications work is very simple because the knowledge is already known

in advance. This paper presents a technology demonstrator to verify a proposed framework

required to support such a not .

Keywords

Artificial Intelligence, Artificial Intelligence Mark up Language , Chatbot , JAVA , ELIZA , Human-

Computer Interaction , Content , Question Answering .

1 . Introduction

Since 2016 the world became digital with the new technology. One of the best example is chatbot. The

chatbot matches the input sentences from the users with in the pattern that I already present in the

knowledge Base (KB). Each pattern is paired with the knowledge base of the chatbot whose primary

source is AIML.

The data which has been modelled on the pattern of the conversations would be tested using a series of

scenarios. The result from the chatbot would be cross checked with the basic pattern defined in AIML

flies. This is done to add some knowledge to the data because it hasn’t been modelled before. So if the

input the output sentences do not match in the knowledge based then it is remodelled.

Chatbot will give solutions for the users queries and problems. In this paper a chatbot is designed to

answers both general questions and FAQ’s. AIML is the artificial markup language. The AIML template

is defined with almost all the general queries like “Hi, Hello, How are you?”etc.

It is used to deal with general questions and greetings. AIML simple language, which can give random

poses for single query (or) scripts.

JASC: Journal of Applied Science and Computations

Volume VI, Issue I, January/2019

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mailto:[email protected],[email protected],[email protected]

mailto:[email protected],[email protected]

Chat box can be built on any closed platform which may support PL ,that allows to make a web API.

Programming language.

Figure 1. Working Of Chatbot.

Figure 2. Chatbot in different domain



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Figure 3. Microsoft Bot Framework

Figure 4. Behavior of Chatbot

2 . Literature Survey or Relevant Work

There are many techniques and others services such as speech to text ,text to speech and natural

language processing etc....,where the bot can be interactive. Kader et al. Presents the design technique’s

for developing interactive Chatbot such as NLTK which can be used to analysis speech and make the bot

response intelligently. They have done the survey of nine selected studies and also discussed the

comparison between the Chatbot designed techniques.

The author has discussed the different chatbot strategies and also compared the conversion techniques

such as text base and speech based conversion. They also discussed some parameters which affects



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human-computer interaction quality in conversation system which can be used to designed web interface.

Now-a-days many different many different chatbot are formed through the web. Many authors have

described their own chatbot platform like “just.chat” which can be used to process the information for

developing the chatbot. And they also discussed “Ed-gar” platform which is designed for the answering

natural language question.

Cloud services are separating its application from its hardware and software are dependence. There are

many cloud service providers including Microsoft and Google and Amazon web services etc .

Nowadays many cloud platforms provide the bot services where we can develop the bot and deploy to

any one of the cloud. there are some cloud-platforms which provide difference services apart from the

bot service such as artificial intelligence. Microsoft bot frame work consist of bot builder, bot connector,

bot directory. it also has an emulator where we can test the working of the bot. if we want our bot to be

more interactive, we can incorporate Microsoft cognitive services such as Language Understanding

Intelligence Services (LUIS).

The responsibility of bot connector is to connect with different channels some of which are Facebook ,

Skype , web chat etc. once the bot is built next job is to publish and deploy the bot to the Microsoft cloud

platform.

Figure 5. System Architecture



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Figure 6. Application of Bot

Figure 7. Flowchart for users of Chatbot



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3 . Analysis

The Mani analysis so that the study of significant difference in both psychological and declarative

response of study participants would de revealed in relation to the type of bot with which the participants

interacted. These different were expected to depend on the type of the entity with which the types of

groups were interacting .We have also discussed the supported cloud platform to build a chatbot. There

are many advantages and disadvantages of the cloud platform based on their functions abilities and

features .using a chatbot in an Enterprise comes with a benefits.

Figure 8. Benifits on Chatbot

Figure 9. Components of Chatbot



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Figure 10. Expert System Engine

Figure 11. Evolution of AI



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Figure 12. Responces Bases on Intelligence

Figure 13. Business Functions on different sectors



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4 . Conclusion

Making an empty into the chatbot spectrum may seen fairly simple and straight forward to

accomplish todaywith the varied technology and tools availableenterprises can enable a customer

service that never ,quickly and effectively. However it is very important to enable good customer

service that never sleeps and not just a redumatorychatbot that is available certainly enterprise

will always have a lot of expectations from chatbot , gives the hope that surrounds this as a

concept.

But it is imperative that well designed and comprehensive bots are developed ,to facilitate

reaching the customers anywhere and anything and via tools where they spent most of their time

has discussed in those paper, they are various aspects to take into consideration in the entire life

cycle of developing and launching a not and all phases of life cycle are important and significant

toward creating a not that works well .

The success of bots in future in the future realize on the ability to be intelligent know their uses,

and know when to stop and most importantly n constantly learn and improve based on the

experience on users .while the true future of chatbots is hard to predict at this point, there is no

taking away from the fact that they are significant part digital transformation of future.

The usage of chatbot will triple through 2019 has interpresis seek to increase customers

satisfaction and reduce operating costs. The bot revolution might evolve into something very

different from what we see it has today. But from where we are today and from where we are

today and based on the potential of bots .



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5 . References

[1] Nicole Radzinill and Morgan Benton et al.,”Evaluating quality of Chabot and

Intelligentconversational agents”.

[2] InlaidNican and Oliver a.tazl and Franz Wotama et I’ll.,”Chabot bases tourist

Reconnedsations using models”,pp(1 -6).

[3] ZojanMemon, AkhtalHussain Jalbani et all.,”Multi-agent communication systems with

Chabot(2017).

[4] MohsinShaikh ,Raphi and Ahmed Ali et al.,” multi-agent communication system with

Chabot(2018).

[5] Michele L ,MC Nepal and David new year et al.,”Chabot in library”,(2013) pp(5-10).

[6] RithikaMessialukasNessiahdas,NeetGupta Debanjan DC Sarkar et al.,”AI-

automationchatbot”,(2018).

[7] AmeyaVichare, AnkulGyami,YashikaShrikhade, NileshRathod et al.,”achatbot system

demonstrating intelligent behavior using NCP”,volume 4,Issue 10 ,(2015).

[8] AM Rahman,addulah AC Mamum,AmarIS lam et all.,”programmingchallenges of

ofchatbot“,(2017) pp(75-78).

[9] Amit patil ,k marimuthn,nagarajarao and niranchaua et all.,”compraatinoal study cloud

platforms to developed a chatbot “,6(3)(2017)pp(57-61).

[10] SarthakV.doshi ,SupradhaB.payarAkshayg.shelal, et all.,”Artificial intelligentChatbot in

android system min OSP “, volum6 ,issue 4 ,



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