issue 2


Sanket Gadge


Modh. Arbaj Ali


Ashwin Sahu


Computer  Department, Mumbai  University
Padmabhushan Vasantdada Patil Pratishthan College Of Engineering

Guided By

Prof. Atul Shintre


In the field of Web Development, user interfaces that can be used includes command line, graphical user interface (GUI), menu driven, form-based, natural language, etc. The mainstream user interfaces include GUI and web-based, but occasionally the need for an alternative user interface arises. A chat bot based conversational user interface fits into this space. The chatbot is a class of bots that have existed in the chat platforms. The user can interact with them via graphical interfaces or widgets, and the trend is in this direction. They generally provide a stateful service i.e. the application saves data of each session. On a college’s website, one often doesn’t know  here to search for some kind of information. It becomes difficult to extract information for a person who is not a student or employee there. The solution to these comes up with a college inquiry chat bot, a fast, standard and informative widget to enhance a college website’s user experience and provide effective information to the user. Chat bots are an intelligent system being developed using artificial intelligence (AI) and natural language processing (NLP) algorithms. It has an effective user interface and answers the queries related to examination cell, admission, academics, users’ attendance and grade point average, placement cell and other miscellaneous activities.

Keywords Artificial intelligence (AI),  knowledge base (KB), natural language processing (NLP), graphical user interface(GUI).

 I. Introduction

Our chatbot is a computer program that can talk to humans in natural language, the way we interact with each other. It can replace a human for many tasks of answering queries. A chatbot is an agent that interacts with users using natural language. It was built as an attempt to fool humans. Several applications of chatbots such as Customer Service, call centers etc. uses Artificial Intelligence Mark-up Language to chat with users.

One of the prime goals of chatbots is to resemble an intelligent human and make it difficult for the receiver of the conversation to understand the real working along with various architecture and capabilities for their usage has widely broadened.

II. Objectives of project

  1. To analyze users queries and understand users’ messages.
  2. To provide an answer to the query of the user very effectively.
  3. To save the time of the user since s/he does not have to personally go to the college for inquiry.
  4. This system will help the student to be updated about the college activities.
  5. The system will reply using an effective GUI which implies that as if a real person is talking to the user.

III. Features of the project

  • College admission related queries could be answered through it.
  • Viewing user profiles and retrieves attendance and grade/ pointers.
  • College students can get information about examinations to be held.
  • College students can fetch particulars about placement activities.

IV. Scope Of The Project

Simple chat bots were capable of matching a text string and offering an answer only when the exact match is found. When we said chatbots have come a long way, we actually meant it. The advanced chatbots today have a learning curve powered by artificial intelligence and are leading them to be of great significance.

The availability of chat bots 24/7 with the immense knowledge they can hold is all set to outperform humans. With speed and accuracy, they are offering support to enterprises, they will soon augment human capabilities. Users love to interact with chat bots as it saves them time and in most cases offers them clear and concrete answers. They may not be perfect but they are scary close to be perfect.

V. Literature survey

Eliza is considered as the first Chatbot, which works on the pattern matching system. It was developed by Joseph Weizenbaum in 1964. ALICE is a rule-based chatbot based on the Artificial Intelligence Markup Language (AIML). It has more than 40,000 categories, where each category has a combination of pattern and its response. Md. Shahriare Satu and Shamim-AI-Mamun showed the review of applications of

the Chatbot which are developed using the AIML scripts. They said that AIML based chatbots are easy to implement,  they are lightweight and efficient to work. Their paper gives the detailed information about the different applications of the chatbots. Thomas N. T. and Amrita Vishwa designed an AIML and LSA based chatbot to provide the customer care service over the E- commerce websites.

 Maja Pantic, Reinier Zwitserloot, and Robbert Jan Grootjans, “Teaching Introductory Artificial Intelligence using A simple Agent Framework”, IEEE Transactions on Education, Vol. 48, No. 3, August 2005. This paper describes a flexible method of teaching introductory artificial intelligence (AI) using a novel, Java-implements simple agent framework developed specifically for the purposes of this course .Although numerous agent frameworks have been proposed in the vast body of literature, none of these available frameworks proved to be simple enough to be used by first-year students of computer science.

VI. Existing System

ALICE  (Artificial  Linguistic  Internet  Computer  Entity) is   inspired    by    Eliza bot, or simply Alice, is a natural language processing chatbot—a program that engages in conversation with a human by applying some heuristic pattern matching rules to the human’s input. It was inspired by Joseph Weizenbaum’s classical ELIZA program. The program is unable to pass the Turing test, as even the casual user will often expose its mechanistic aspects in short conversations.

No such chatbot exists on our college website as we felt there is a need for it from a student point of view and faculty will be benefited more as they only have to do the work once.

VII. Need For New  System

Eliza is considered as the first Chatbot, which works on the pattern matching system. It was developed by Joseph Weizenbaum in 1964 The need for a college inquiry system arises due to various reasons which include: the slow nature of the college website, an outsider would not know where to search for a particular piece of information, difficult for the person outside the college’s domain to extract information. The smart solution for all the drawbacks lends to the need of the system. The college inquiry system will provide the response by summarizing the query and then output answers, it also provides selective information about what the user wants. A college system will dispense all answers relating to domains such as admission, examination cell, notice board, attendance, placement cell and other miscellaneous domains.

VIII. Work Flow Of The Project

IX. Output

X. Conclusions

Artificial Intelligent is the fastest growing technology everywhere in the word. With the help of Artificial Intelligent and Knowledgeable databases. We can make the transformation in the pattern matching and virtual assistance. This system is developing chat bot based on a web based system so with the combination of Artificial Intelligent Knowledgeable database and virtual assistance. We can develop such chat bot which will make a conversion between human and machine and will satisfy the question raised by the user.


  1. AI BASED CHATBOT Prof.Nikita Hatwar 1, Ashwini Patil , Diksha Gondane 3 123 (Information Technology, Priyadarshini College of Engineering,Nagpur/ RTMNU,India)International Journal of Emerging Trends in Engineering and Basic Sciences (IJEEBS) ISSN (Online) 2349-6967 Volume 3, Issue 2 (March-April 2016)
  2. Y. Wu, G. Wang, W. Li, and Z. Li, “Automatic Chatbot Knowledge Acquisition from Online Forum via Rough Set and Ensemble Learning,” Proc. IEEE of 2008 IFIP International Conference on Network and Parallel Computing, 2008, pp. 242-246, doi:10.1109/NPC.2008.24.
  3.  J. Bang, H. Noh, Y. Kim and G. G. Lee, “Example-based chatoriented dialogue system with personalized long-term memory,”2015 International Conference on Big Data and Smart Computing (BIGCOMP), Jeju, 2015.
  4. Y. Chen, W. Wang and Z. Liu, “Keyword-based search and exploration on databases,” 2011 IEEE 27th International Conference on Data Engineering, Hannover, 2011.
  5. AIML Interpreter Overview 2004,
  6. Computing machinery and intelligence, Alan Turing [1950],
  7. Using Dialogue Corpora to Train a Chatbot (Bayan Abu Shawar, Eric Atwell)

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