scholarly journals The Concept of Data Mining

2021 ◽  
Author(s):  
Julius Olufemi Ogunleye
Keyword(s):  
Data Mining ◽  
Data Storage ◽  
Data Centers ◽  
Data Sources ◽  
The Internet ◽  
Data Mining Techniques

Data mining is a technique for identifying patterns in large amounts of data and information. Databases, data centers, the internet, and other data storage formats; or data that is dynamically streaming into the network are examples of data sources. This paper provides an overview of the data mining process, as well as its benefits and drawbacks, as well as data mining methodologies and tasks. This study also discusses data mining techniques in terms of their features, benefits, drawbacks, and application areas.

Data Mining Techniques and Applications

2018 ◽  
Vol 9 (1) ◽  
pp. 78-97 ◽  
Author(s):  
Nayem Rahman
Keyword(s):  
Data Mining ◽  
Social Media ◽  
Unstructured Data ◽  
The Internet ◽  
Holistic View ◽  
Data Mining Techniques ◽  
Extant Literature ◽  
Business Environments ◽  
Data Volume ◽  
Complete Set

Data mining has been gaining attention with the complex business environments, as a rapid increase of data volume and the ubiquitous nature of data in this age of the internet and social media. Organizations are interested in making informed decisions with a complete set of data including structured and unstructured data that originate both internally and externally. Different data mining techniques have evolved over the last two decades. To solve a wide variety of business problems, different data mining techniques are developed. Practitioners and researchers in industry and academia continuously develop and experiment varieties of data mining techniques. This article provides an overview of data mining techniques that are widely used in different fields to discover knowledge and solve business problems. This article provides an update on data mining techniques based on extant literature as of 2018. That might help practitioners and researchers to have a holistic view of data mining techniques.

Informational Data Mining

2013 ◽  
pp. 58-65
Author(s):  
Feyza Gürbüz ◽  
Fatma Gökçe Önen
Keyword(s):  
Data Mining ◽  
Information Systems ◽  
Knowledge Discovery ◽  
Major Change ◽  
Research Community ◽  
Data Sources ◽  
Accurate Information ◽  
Rule Mining ◽  
Data Mining Techniques ◽  
Information Strategies

The previous decades have witnessed major change within the Information Systems (IS) environment with a corresponding emphasis on the importance of specifying timely and accurate information strategies. Currently, there is an increasing interest in data mining and information systems optimization. Therefore, it makes data mining for optimization of information systems a new and growing research community. This chapter surveys the application of data mining to optimization of information systems. These systems have different data sources and accordingly different objectives for knowledge discovery. After the preprocessing stage, data mining techniques can be applied on the suitable data for the objective of the information systems. These techniques are prediction, classification, association rule mining, statistics and visualization, clustering and outlier detection.

scholarly journals Research of various Data Mining Techniques for IoT Applications

2019 ◽  
Vol 8 (2S11) ◽  
pp. 1083-1086
Keyword(s):  
Data Mining ◽  
Data Analysis ◽  
Internet Of Things ◽  
Important Task ◽  
The Internet ◽  
Huge Amount ◽  
Data Mining Techniques ◽  
Amount Of Information ◽  
Iot Applications ◽  
Iot Devices

In recent years everything is connected and passing through the internet, but Internet of Things (IOT), which will change all aspects of our lives and future. While the things are connected to the internet, they will generate the huge amount of information which has to be processed. The information that gathered from various IoT devices has to be recognized and organized according to the environments of their type. To recognize and organize the data gathered from different things, the important task to be played is making things passing through different Data Mining Techniques (DMT). In this article, we mainly focus on analysis of various Data Mining Techniques over the data that has been generated by the IOT Devices which are connected over the internet using DBSCAN Technique. And also performed review over different Data Mining Techniques for Data Analysis

Data Mining Techniques for Distributed Denial of Service Attacks Detection in the Internet of Things

2016 ◽  
pp. 275-334 ◽  
Author(s):  
Pheeha Machaka ◽  
Fulufhelo Nelwamondo
Keyword(s):  
Data Mining ◽  
Internet Of Things ◽  
Denial Of Service ◽  
Current Data ◽  
The Internet ◽  
Denial Of Service Attacks ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Data Mining Techniques ◽  
The Internet Of Things

This chapter reviews the evolution of the traditional internet into the Internet of Things (IoT). The characteristics and application of the IoT are also reviewed, together with its security concerns in terms of distributed denial of service attacks. The chapter further investigates the state-of-the-art in data mining techniques for Distributed Denial of Service (DDoS) attacks targeting the various infrastructures. The chapter explores the characteristics and pervasiveness of DDoS attacks. It also explores the motives, mechanisms and techniques used to execute a DDoS attack. The chapter further investigates the current data mining techniques that are used to combat and detect these attacks, their advantages and disadvantages are explored. Future direction of the research is also provided.

Analysising on the Library Services in the Age of Big Data

2014 ◽  
Vol 1044-1045 ◽  
pp. 1066-1070
Author(s):  
Chen Wei ◽  
Xiao Di Wang ◽  
Ran Ma ◽  
Bing Qi Wang
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Data Analysis ◽  
Social Networking ◽  
Data Storage ◽  
Rapid Development ◽  
Structured Data ◽  
The Internet ◽  
Library Services ◽  
Library Service

The advent of the age of big data brings not only the rapid development of the Internet, scientific research, social networking and other fields, but also help and challenges to the application of library. For example, the library service applications in data storage, data mining, data analysis, etc. can identify hidden values behind the data only through systematic organization and analysis of massive structured, unstructured, and semi-structured data, ​​in order to predict the future development of library and promote its better development.

Research and Application in the Web Data Mining Based on the XML

2014 ◽  
Vol 644-650 ◽  
pp. 2124-2127
Author(s):  
Fen Liu
Keyword(s):  
Data Mining ◽  
Information Transmission ◽  
Rapid Development ◽  
Data Sources ◽  
The Internet ◽  
Web Data ◽  
Web Data Mining ◽  
Mining Technology ◽  
Web Documents ◽  
The Web

With the rapid development of Internet, the Internet has become the important resources of information transmission and share. The characteristics of Web data are semi-structured, heterogeneous and mass, making traditional data mining technology indirectly applied to Web data sources. Web data mining refers to extracting a potential, useful model from the Web documents or Web activities. Because of the structural and expansibility of XML, research on XML combined with Web data mining has also became popular.

scholarly journals Employing Data Mining Techniques in Testing the Effectiveness of Modernization Theory

2016 ◽  
Vol 2 (1) ◽  
pp. 98
Author(s):  
Tolga Aydın
Keyword(s):  
Data Mining ◽  
Economic Development ◽  
Mobile Phone ◽  
Important Variable ◽  
The Internet ◽  
Modernization Theory ◽  
Data Mining Techniques ◽  
Mobile Phone Usage ◽  
Using Data ◽  
New Variables

This interdisciplinary study is concerned with testing the effectiveness of Modernization Theory in explaining regime change by means of data mining techniques. Modernization Theory, which links democratization with economic development (improvements in income, urbanization, industrialization, education and communication levels), has been criticized widely. Many criticisms posited that there is not a significant relation between economic development and democratization. This study is an attempt to test whether the theory has improved its effectiveness with the advent of the Internet and mobile phone technologies. To this end, first, the variables are introduced. Then, the study makes an analysis by using data mining techniques. It first tests the correlation between democratization and improvements in income, education, urbanization and communication levels within the period between 1976 and 1995. Then it adds the new variables, the Internet and mobile phone usage, and tests the correlation between democratization and this new range of variables for 1996-2015 period. In the conclusion, the study evaluates whether the effectiveness of Modernization Theory is improved when the Internet and mobile phone usage are added as the new variables. It is found that there is not a strong relation between income per capita and democratization as some critics of the Modernization Theory suggest, but other factors emphasized by this theory like improvements in education and communication have a more decisive effect. Moreover, among our new variables, Internet usage proved to be a really important variable conducive to democratization according to test results.

scholarly journals Review on Technologies Used in Developing a Tool for Automatic Software Upgrades at Data Centers

2021 ◽  
Vol 23 (06) ◽  
pp. 767-774
Author(s):  
Niveditha. V.K ◽  
◽  
Dr. Kiran. V ◽  
Avinash Pathak ◽  
◽  
...  
Keyword(s):  
Data Storage ◽  
Data Centers ◽  
The Internet ◽  
Software Upgrades ◽  
Huge Data ◽  
Wide Range ◽  
Automatic Software ◽  
Software Upgrade ◽  
The Internet Of Things ◽  
Fast Evolution

The fast evolution pace of various technologies such as the Internet of Things (IoT), Cloud Computing and the world moving towards digitalization created an increased need for data centers than ever before. Data centers support a wide range of internet services, including web hosting, e-commerce, and social networking. In recent years huge data centers have been owned and run by tech giants like Google, Facebook, Microsoft, etc., and these firms are known as Hyper-scalers. Hyper-scalers are the next big thing, ready to fundamentally alter the internet world for data storage through a variety of services supplied by them across all technological domains. The tool for automatic software upgrade focuses on having a seamless upgrade for the devices in the datacenters mainly in huge data centers owned by the hyper-scalers. This paper mainly focuses on the technologies used in developing the tool for automatic software upgrade, an overview of how the tool is developed, and its features. By deploying this tool in the datacenters, it supports them in delivering more efficient services.

scholarly journals PREDICTIVE MODELING OF TECHNOLOGICAL DEVELOPMENT TRENDS

2020 ◽  
Vol 55 ◽  
pp. 103-108
Author(s):  
Alla G. Kravets ◽  
◽  
Natalia A. Salnikova ◽  
Keyword(s):  
Neural Network ◽  
Data Mining ◽  
Predictive Modeling ◽  
Technological Development ◽  
Data Sources ◽  
Development Trends ◽  
Data Mining Techniques ◽  
The Neural Network ◽  
Existing Data

In the work, the problem of forecasting technological development trends was considered. A review of the sources of the global patent space, an analysis of technological development trends, a survey of data sources for training the neural network were carried out. Existing data mining techniques were analyzed for more accurate and faster forecasting. A module for predictive modeling of trends in technological development was developed, algorithms for the module for predictive modeling of trends in technological development were described.

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