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Wednesday, 27 June 2018

AIML Based Human Interaction Bot on Android Operating System

Abstract:

 It is artificial intelligence based chatbot using AIML built on Android. It presents the conversational system between human and computer using natural language processing. As an enhancement to well-known conversational agents like chatbots, in the proposed setting, the dialog between human and machine is intended as a query/answer monotonic process whose goal is reducing semantic ambiguity within communication and delivering the required output. The popularity of chatbots has made it useful in great variety of applications. This application will interact with the users and provide solutions to the problems. Artificial Intelligence Markup Language (AIML) comes from Extensible Markup Language (XML) which is used to build up artificial intelligence bots. In this project, AIML language is used for intelligent conversation between human and machine.

Keywords: Chatbot ,AIML, ALICE,Android.

INTRODUCTION

The chatbot is an agent where the computer program is designed to have an intelligent conversation with the user. But to do this, AIML language is used as it is efficient and lightweight.. ALICE is the most popular open source AIML based chatbot which won Leobner Price three times (2000,2001, and 2004). So, now a day, various kinds of organizations are interested to implements AIML based chatbot to get conversation with customers with minimum configuration and cost. In tills paper, we focus on several applications whose implements AIML based chatbot with additional software packages to develop efficient applications. It exists a grammar based parsing which helps to understand the sentence intended by the user.. The efficiency of the parsing strictly depends on the complexity of the grammar involved. Polynomial-time parsers are largely available for context-free languages, which represent the formal base for most programming languages. In this paper, a dialogue-oriented technique for chat-based interface is presented. User can request for services in natural language by chatting with the system. If the content of the message is correctly interpreted, the corresponding service is delivered, otherwise a dialogue is instantiated to disambiguate the meaning of the request. The challenge of the proposed system is twofold:

 1. make the HCI resemble an ordinary human-human conversation as much as possible;

2. let the user converge towards an unambiguous query formulation. First point is obtained with the system providing disambiguated alternatives to user and asking him/her for missing pieces of information; the second point is fulfilled by reckoning a semantic score that allows for measuring the actual distance between the user query and the query interpretations performed by the system.

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