Chatbot for University Related FAQs

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Aim:

This paper aims to address the automated response in University FAQ chat to mimic the presence of the real human.

Existing System:

AIML and LSA are used for creating chatbots. AIML is Artificial Intelligence Markup Language and Latent Semantic Analysis are used for developing chatbots, which are used to define general queries like how do you do?, how can I help you etc. This pattern can also be used to give random responses for same query. LSA is a Latent Semantic Analysis, which is utilized to discover likenesses between words as vector representation. So that the unanswered queries by AIML will be viewed as a reply by LSA. Most chatbots basically search for keywords, phrases, and examples that have been customized into their databases, yet some utilize more propelled strategies. So far no chatbot has possessed the capacity to totally trick people into trusting it as one of them through its information of regular dialect.

Proposed System:

Chatbot is a manufactured substance that is intended to reproduce a clever discussion with human accomplices through their regular language. Currently, chatbots are utilized by a great many web clients to intercede access to information or learning bases and furthermore to do no specific discussions. We propose a new system to implement effective chatbot for university FAQ using machine learning. The dataset, the question and answers to be processed for chat bit automation is prepared. The dataset is processed to find out the root words of the given sentences or question by the user. We also calculate the parts of speech of a sentence using Stemming algorithm and parse of Stanford University. The resultant text was used to train the system. A chatbot is created using python web library.