Knowledge base construction, knowledge representation in neo4j and implementation UI in voice user interfaced intelligent interview chatbot

A chatbot is a program that communicates with human. It is powered by Machine Learning,
more commonly it is driven using intelligent rules. The term chatbot is synonymous with text
conversation but is growing quickly through voice communication. Chat interface may be
conversational or voice user interfaced chatbot. Natural language processing technology was
good enough to understand all kinds of user requests.NLP is a way for computers to analyze,
understand and derive meaning from human language in a smart and useful way .A
conversational UI gives the privilege of interacting with the computer. It allows a user to tell the
computer what to do. It takes two forms i.e., voice assistant that allows you to talk and chatbots
that allow you to type. First, conversational interfaces are text based dialog systems for question
answering and conversational chatbots. Then the speech based dialog systems began to appear.
I-aBro is a Voice user interfaced neo4j data-driven intelligent interviewer
chatbot. I-aBro uses both Rule based and Generative based chatbot. One function is based on the
set of rules and the other more advanced version uses Machine Learning. It generates questions
automatically. Named Entity Recognition technology is used to generate the question, which
made more reliable interview approach. Question Generation is fully relying on user inputs that
mean question is generated by the previous response of the user. Scoring and evaluation is the
another main advantage of the I-aBro system. Chat-log is converted to PDF format and it sent via
mail to the close group of experts for evaluation is one method. And another method is
evaluation by system itself. This approach is based on the syntactic similarity of candidate
response and knowledge present in knowledge base.

MSC MI 2016-2018 INT Dr. Asharaf S