Question

CRM (Customer Relationship management)

What is Sentiment Analysis?

What are expert systems?

Tree terms Fuzzy Logic, genetic algorithms and neural networks?

Answer 1

Definitions and understanding of these terms is quite simple but each of them is a complete subject to learn.

Sentiment Analysis: Sentiment analysis is contextual mining of text which identifies and extracts subjective information in source material, and helping a business to understand the social sentiment of their brand, product or service.

example twitter sentiment analysis of tweets

Expert Systems: In artificial intelligence, an expert system is a computer system that has/develops the decision-making ability of a human expert. Expert systems are designed to solve complex problems by reasoning through bodies of knowledge, represented mainly as if–then rules rather than through conventional procedural code.

Fuzzy logic: Fuzzy logic is a form of many-valued logic in which the truth values of variables may be any real number between 0 and 1 both inclusive. It is employed to handle the concept of partial truth, where the truth value may range between completely true and completely false.It is different in the way that it allows values to be more accurate than on or off. While boolean logic only allows true or false, fuzzy logic allows all things in between.

Genetic Algorithms: A genetic algorithm is a heuristic search method used in artificial intelligence and computing. It is used for finding optimized solutions to search problems based on the theory of natural selection and evolutionary biology. Genetic algorithms are excellent for searching through large and complex data sets. At each step, the genetic algorithm uses the current population to create the children that make up the next generation. The algorithm selects a group of individuals in the current population, called parents, who contribute their genes—the entries of their vectors—to their children.

Neural Network : The purpose of a neural network is to learn to recognize patterns in your data. Once the neural network has been trained on samples of your data, it can make predictions by detecting similar patterns in future data.It has the ability to learn , recall and generalize from the given data by suitable assignment and adjustment of weights. The collective behavior of the neurons describes its computational power, and no single neuron carries specific information

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