A Summarized Report on Data Mining and It’s Essential Algorithms

International Journal of Academic Research in Business and Social Sciences, 2022

Nowadays, some of the intersting roles of human life are data, information, and knowledge. Analyzing and modelling of big data have been required by data massive storehouses together with the rapid technologies growth to predict and analyze the future trends of information. Methodologies and techniques, which are employed into diverse information systems scope, are needed for detection of knowing in the databases. The technology which extracts advantageous information to discover knowledge is called Data Mining. Data mining, it has been defined as discovery of knowledge in data (KDD), it is the disclosure of modalities procedures and other valuable information from considerable sets of data. It has been a tremendous progress in machine learning, artificial agent systems, and decision-making in the expert systems. In the last decades, most of the techniques and applications has been surveyed via the researchers. Those techniques and applications are utilized in distinct areas in daily life like industrialization, education, engineering, commerce and business. Searching last years researches about the review of the most techniques and trends of data mining in multiple areas was the method which is followed in this paper. It has discovered in the learning field as diffusing data mining for educating activities, improvement quality of tasks into manufacturing field, text mining as a technique into research databases and so on. This study collectes a summary of information about the basci concept of Data Mining and its technques which other researchers may need to start their studies in Data Mining field.

With progression in technology specifically in last three decades or so, an enormous magnitude of information has been transitioned into a digital form, which resulted in formation of enormous data repositories. With accrual of information in these repositories a challenge persisted as how to extract meaningful knowledge from it. Data mining as a tool was used to tackle the situation. Data mining considered as stepping stone to procedure of knowledge discovery in databases, this is a procedure of extracting hidden information from enormous sets of databases to excavate eloquent patterns and rules. Data mining has now become an indispensable component in almost every field of human life. The present article provides an analysis of the available literature on data mining. The concept of data mining as well as its various methodologies are summarized. Some applications, tasks and issues related to it have also been illustrated.

Data mining is the computational process of discovering patterns in large data sets. The overall goal of the data mining process is to extract information from a data set and transform it into an understandable structure for further use. The paper discusses few of the data mining techniques, algorithms and some of the organizations which have adapted data mining technology to improve their businesses and found excellent results and focuses on presenting the applications of data mining in the business environment.

Data mining is an extraction of knowledge discovery from huge amount of data which is previously unknown and potentially useful for analytical processing and decision making. The other acronyms of data mining are such as Data archeology, Data dredging, Information harvesting and Business Intelligence. The various data mining techniques are used to find the hidden interestingness or new patter to store the data. These techniques and approaches of data mining can efficiently build the new environment for analyzing and predictions. This paper highlights data mining process and its various techniques to find the interestingness. Finally, concluded with its limitations. The objective of the paper is opens new horizons for researchers of forthcoming generations.

Data mining is a field of research which is escalating gradually. Data mining is the method of analyze data from unique views and summarization it interested in useful data. "Data mining, also in general referred to like knowledge discovery from data (KDD), is the computerize or suitable extraction of patterns in place of knowledge completely stored or captured in large databases, data warehouse, the web, other vast information repositories or information streams". Data mining machine works with data warehouse and the whole process is divided into action plan to be performed on data: selection, transformation, mining and results elucidation. In this term paper, we have reviewed equal types of obedience in data mining, also make clear different areas somewhere used data mining feeling and used of it.

Data and Information or Knowledge has a significant role on human activities. Data mining is the knowledge discovery process by analyzing the large volumes of data from various perspectives and summarizing it into useful information. Due to the importance of extracting knowledge/information from the large data repositories, data mining has become an essential component in various fields of human life. Advancements in Statistics, Machine Learning, Artificial Intelligence, Pattern Recognition and Computation capabilities have evolved the present day’s data mining applications and these applications have enriched the various fields of human life including business, education, medical, scientific etc. Hence, this paper discusses the various improvements in the field of data mining from past to the present and explores the future trends.

Sigmod Record, 2002

Mining information from data: A presentday gold rush. Data Mining is a multidisciplinary field which supports knowledge workers who try to extract information in our "data rich, information poor" environment. Its name stems from the idea of mining knowledge from large amounts of data. The tools it provides assist us in the discovery of relevant information through a wide range of data analysis techniques. Any method used to extract patterns from a given data source is considered to be a data mining technique.

—Data mining an non-trivial extraction of novel, implicit, and actionable knowledge from large data sets is an evolving technology which is a direct result of the increasing use of computer databases in order to store and retrieve information effectively .It is also known as Knowledge Discovery in Databases (KDD) and enables data exploration, data analysis, and data visualization of huge databases at a high level of abstraction, without a specific hypothesis in mind. The working of data mining is understood by using a method called modeling with it to make predictions. Data mining techniques are results of long process of research and product development and include artificial neural networks, decision trees and genetic algorithms. This paper surveys the data mining technology, its definition, motivation, its process and architecture, kind of data mined, functionalities and classification of data mining, major issues, applications and directions for further research of data mining technology.

Data mining is a procedure of mining information from huge set of heterogeneous data which is scattered over different storage repositories, smart devices, internet of things etc. In this paper, we have discussed about various Data Mining techniques viz classification, clustering, regression and decision tree. We have also discussed use of various data mining applications in financial analysis, health care, fraud detection and prevention, telecommunication industries, science and engineering.

International Journal of Software & Hardware Research in Engineering

Data mining is the process of bring out the information from huge amount of data. Data mining is also referred as Knowledge Discovery from the Data(KDD), it is the convenient extraction of patterns representing knowledge implicitly stored or captured in Large Databases, Data Warehouses, the Web, other massive Data Repositories or Information Streams. In this paper we have discourse various Data Mining Concepts, Process, Techniques and Data Mining Applications.

2014

Data mining is a process of using different algorithms to find useful patterns or models from data. It is a process of selecting, exploring and modeling large amount of data. Mostly used in technology and also used in different areas of real life like finance, marketing, business. It can also be used in different social science methodologies, such as psychology, cognitive science and human behavior etc. The ability to continually change and acquire new understanding is a driving force for the application of DM. This allows many new future applications of data mining (1) as in today's world the need of data in every field is growing very vast. So, for satisfying our need there should be proper Data Mining techniques available. In this paper we are presenting valuable information about data mining.

International Journal on Recent and Innovation Trends in Computing and Communication

Data mining is the process of identification of the patterns and trends in large and complex data volumes. The normal data processing will not be helpful in handling such complex data. Hence data mining is used to handle such large volumes of the data. This paper will explain the steps of data mining process, types of data mining. It will also explain the importance and advantages of the data mining and challenges involved in the implementation of the data mining.

International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2022

Data mining is a powerful new technology with great potential to help companies focus on the most important information in their data warehouses. It is well-known that data mining is a significant sub-field of knowledge management and that it is one of the most important information exploration phases in the database cycle. Over the ensuing decades, the practice of data mining will increase in market and learning companies. An introduction to the fundamentals of data mining is provided in this paper.

International Journal of Distributed and Parallel systems, 2010

In the Information Technology era information plays vital role in every sphere of the human life. It is very important to gather data from different data sources, store and maintain the data, generate information, generate knowledge and disseminate data, information and knowledge to every stakeholder. Due to vast use of computers and electronics devices and tremendous growth in computing power and storage capacity, there is explosive growth in data collection. The storing of the data in data warehouse enables entire enterprise to access a reliable current database. To analyze this vast amount of data and drawing fruitful conclusions and inferences it needs the special tools called data mining tools. This paper gives overview of the data mining systems and some of its applications.