Developing a Chatbot using Machine Learning
K. Jwala1, G.N.V.G Sirisha2, G.V. Padma Raju3
1K. Jwala, Department of Computer Science and Engineering, S.R.K.R. Engineering College, Bhimavaram (Andhra Pradesh), India.
2G.V. Padma Raju, Department of Computer Science and Engineering, S.R.K.R. Engineering College, Bhimavaram (Andhra Pradesh), India.
3G.N.V.G. Sirisha, Department of Computer Science and Engineering, S.R.K.R. Engineering College, Bhimavaram (Andhra Pradesh), India.
Manuscript received on 11 May 2019 | Revised Manuscript received on 05 June 2019 | Manuscript Published on 15 June 2019 | PP: 89-92 | Volume-8 Issue-1S3 June 2019 | Retrieval Number: A10170681S319/2019©BEIESP
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In recent years, the development of chatbot has become trendier and so far several conversational chatbots were designed which replaces the traditional chatbots. A chatbot is a computer program which is used to interact with humans and fulfill their needs. Chatbot gives the response for the user query and sometimes they are capable of executing tasks also. Early development of chatbots became so difficult whereas recent chatbots development is much easier because of the wide availability of development platforms and source code. A chatbot can be developed using either Natural Language Processing (NLP) or Deep Learning. When compared to traditional chatbots, bots designed using Deep Learning requires huge amount of data to train. The aim of this paper is to present, in what different ways the chatbot can be developed and their classifications. This paper also makes a discussion about the metrics for accessing the performance of bots. This helps in designing more effective bots.
Keywords: Chatbots, Deep Learning, Natural Language Processing (NLP), Word Embedding.
Scope of the Article: Machine Learning