A Review Of Clustering Methods Based on Artificial Intelligent Techniques

Abstract

Due to the development in various areas of life, the development of the Internet, and the presence of many datasets, and in order to obtain useful information from the rapidly increasing volumes of digital data, there must be theories and computational tools to help humans extract the useful information they need from this data. Large data is collected from many different services and resources. Clustering is one of the most basic and well-known methods of data mining and extraction and obtaining useful information. The technique of recognizing natural groups or clusters within several datasets based on some measure of similarity is known as data clustering. Many researchers have introduced and developed many clustering algorithms based on the different methods of artificial intelligence techniques. Finding the right algorithms greatly helps in organizing information and extracting the correct answer from different database queries. This paper provides an overview of the different clustering methods using artificial intelligence and finding the appropriate clustering algorithm to process different data sets. We highlight the best-performing clustering algorithm that gives effective and correct clustering for each data set.