scholarly journals ChatBot for College Website

In any service-providing organization, it is necessary to answer current or future customer’s questions for their information and for maintaining good relationship with the customers. These organizations usually have call centers with hundreds and thousands of employees to give replies to customers through chat (i.e. text) or phone calls. These kind of traditional systems need large number of employees which eventually increases the overall expenditure and manpower requirement of that organization. This paper is aimed at minimizing the manpower requirement i.e. decreasing the number of employees by implementing a chat service. This concept of chatbot has been proposed for implementation in College Website that will automatically reply to the queries of stakeholders like students, parents, etc. without any human interaction. For implementation of chatbot sequence to sequence model is used which is a deep neural network

Author(s):  
David T. Wang ◽  
Brady Williamson ◽  
Thomas Eluvathingal ◽  
Bruce Mahoney ◽  
Jennifer Scheler

Author(s):  
P.L. Nikolaev

This article deals with method of binary classification of images with small text on them Classification is based on the fact that the text can have 2 directions – it can be positioned horizontally and read from left to right or it can be turned 180 degrees so the image must be rotated to read the sign. This type of text can be found on the covers of a variety of books, so in case of recognizing the covers, it is necessary first to determine the direction of the text before we will directly recognize it. The article suggests the development of a deep neural network for determination of the text position in the context of book covers recognizing. The results of training and testing of a convolutional neural network on synthetic data as well as the examples of the network functioning on the real data are presented.


2020 ◽  
Author(s):  
Ala Supriya ◽  
Chiluka Venkat ◽  
Aliketti Deepak ◽  
GV Hari Prasad

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