Machine Learning and Artificial Intelligence based Analysis for Top Organization

Abstract

Top organizations doing surveys so they can get to know their rating in between other similar organizations. The Internet provides a platform for organizations to display the details of an organization on their website which is accessible throughout the world, people can see all details about the organization on the internet. They can view the ranking of top organizations and able to compare and analyze the ranking of different top organizations. Clients first see the rating of the organization while joining them and from the customer's point of view organization rating shows the growth of the organization. This proposed paper concept introduces a data mining technique to provide a rating of organization based on customer feedbacks and plot the comparison graph of different organization, for this data mining analysis machine learning (ML) is used for data pre-processing and for self-learning maximum entropy artificial intelligence (AI) algorithm is used, which is helpful to the machine to self-decide word meaning sense like positive, negative or neutral. To get the desired result first step which applied on input data is preprocessing which is mainly used to filter the data based on Machine Learning (ML) concept means it is removing unnecessary part of data from input data. Here it will remove words like is, am, are, was, were, will, will be, etc. Apart from this, it will remove all special characters from a sentence. If any URL is mention in a sentence that is also removed from the sentence. The proposed system of the paper using a maximum entropy algorithm for self-learning of people feedback sentiment to provide ratings of top organizations. In this algorithm, first, we have to pass keyword (meaning full words) it generates numerical values for all keywords and based on threshold value in creating categories range for positive, negative, and neutral sentiment. Based on these categories machine-self recognize the sentiment of the word.