Emotionally Intelligent Chatbot

Shubham Kokane, Shreeyash Khalate, Shreya Newale, Sakshi Dubewar, Jameer Kotwal
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Abstract

Abstract: An emotionally intelligent chatbot system aims to make an effective conversation between humans and machines in as natural and interactive manner as possible. The chatbot agent has pre-embedded knowledge base to identify the sentences, intents, entities and context of the input query to be precise for making a valid, predictable decision itself as a self -generated response to answer the query. The present technical project consists of developing an intelligent system for college enquiry purposes using a web-based chatbot agent, through machine learning, query processing and sentiment and emotion classification system to analyze the sentiment of the visitor towards the college. Emotionally Intelligent College Enquiry Chatbot System is nothing but chatbot to understand the user queries and respond to it during a conversation. Chatbot can actively help human to involve in a digital automated conversation with a machine or a system with effective. In the following proposed system, feature extraction and data cleaning techniques are applied on the dataset and classifiers such as multinomial naive bayes, logistic regression and k nearest neighbors are used to train the model. The classifier with highest accuracy is further used for emotion classification of users.
高情商聊天机器人
摘要:情感智能聊天机器人系统旨在使人与机器之间以尽可能自然和互动的方式进行有效的对话。聊天机器人代理具有预嵌入的知识库,用于识别输入查询的句子、意图、实体和上下文,以精确地做出有效的、可预测的决策,作为自生成的响应来回答查询。目前的技术项目包括使用基于web的聊天机器人代理开发一个大学查询智能系统,通过机器学习、查询处理和情感分类系统来分析访问者对大学的情感。情商大学查询聊天机器人系统只不过是一个聊天机器人,可以理解用户的查询并在对话中做出回应。聊天机器人可以积极地帮助人类与机器或系统进行有效的数字自动对话。在下面提出的系统中,在数据集上应用特征提取和数据清洗技术,并使用多项朴素贝叶斯、逻辑回归和k近邻等分类器来训练模型。将准确率最高的分类器进一步用于用户的情感分类。
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