Combining Different Data Mining Techniques to Improve Data Analysis

2001 ◽  
pp. 455-464
Author(s):  
Sergio Greco ◽  
Elio Masciari ◽  
Luigi Pontieri
Keyword(s):  
Data Mining ◽  
Data Analysis ◽  
Data Mining Techniques

A Systematic Review About Prediction of Academic Behavior Through Data Mining Techniques

2020 ◽  
Vol 17 (11) ◽  
pp. 5162-5166
Author(s):  
Puninder Kaur ◽  
Amandeep Kaur ◽  
Rajwinder Kaur
Keyword(s):  
Systematic Review ◽  
Data Mining ◽  
Data Analysis ◽  
Educational Data Mining ◽  
Prediction Methods ◽  
Time Data ◽  
Academic Behavior ◽  
Data Mining Techniques ◽  
Real Time Data ◽  
Extract Information

In the IT world, predicting the academic performance of the huge student population poses a big challenge. Educational data mining techniques significantly contribute in providing solution to this problem. There are several prediction methods available for data classification and clustering, to extract information and provide accurate results. In this paper, different prediction methodologies are highlighted for the prediction of real-time data analysis of dynamic academic behavior of the students. The main focus is to provide brief knowledge about all data mining techniques and highlight dissimilarities among various methods in order to provide the best results for the students.

A Classification Framework for Data Mining Applications in Criminal Science and Investigations

2020 ◽  
pp. 277-293
Author(s):  
Mahima Goyal ◽  
Vishal Bhatnagar ◽  
Arushi Jain
Keyword(s):  
Data Mining ◽  
Data Analysis ◽  
Data Mining Techniques ◽  
Road Map ◽  
Classification Framework ◽  
Challenges And Opportunities ◽  
Crucial Information ◽  
Tools And Techniques ◽  
Day By Day ◽  
Mining Tools

The importance of data analysis across different domains is growing day by day. This is evident in the fact that crucial information is retrieved through data analysis, using different available tools. The usage of data mining as a tool to uncover the nuggets of critical and crucial information is evident in modern day scenarios. This chapter presents a discussion on the usage of data mining tools and techniques in the area of criminal science and investigations. The application of data mining techniques in criminal science help in understanding the criminal psychology and consequently provides insight into effective measures to curb crime. This chapter provides a state-of-the-art report on the research conducted in this domain of interest by using a classification scheme and providing a road map on the usage of various data mining tools and techniques. Furthermore, the challenges and opportunities in the application of data mining techniques in criminal investigation is explored and detailed in this chapter.

Survey of Data Mining Techniques on Crime Data Analysis

2012 ◽  
Vol 1 (2) ◽  
pp. 47-49 ◽  
Author(s):  
Revatthy Krishnamurthy ◽  
◽  
J. Satheesh Kumar ◽  
Keyword(s):  
Data Mining ◽  
Data Analysis ◽  
Data Mining Techniques ◽  
Crime Data

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

Social Networking Data Analysis Tools and Services

2018 ◽  
pp. 19-34
Author(s):  
Gopal Krishna
Keyword(s):  
Data Mining ◽  
Social Networks ◽  
Data Analysis ◽  
Social Networking ◽  
Data Interpretation ◽  
Product Reviews ◽  
Huge Amount ◽  
Data Mining Techniques ◽  
Business Interests ◽  
Contents Sharing

Social networks have drawn remarkable attention from IT professionals and researchers in data sciences. They are the most popular medium for social interaction. Online social networking (OSN) can be defined as involving networking for fun, business, and communication. Social networks have emerged as universally accepted communication means and boomed in turning this world into a global town. OSN media are generally known for broadcasting information, activities posting, contents sharing, product reviews, online pictures sharing, professional profiling, advertisements and ideas/opinion/sentiment expression, or some other stuff based on business interests. For the analysis of the huge amount of data, data mining techniques are used for identifying the relevant knowledge from the huge amount of data that includes detecting trends, patterns, and rules. Data mining techniques, machine learning, and statistical modeling are used to retrieve the information. For the analysis of the data, three methods are used: data pre-processing, data analysis, and data interpretation.

Social Networking Data Analysis Tools and Services

2021 ◽  
pp. 406-421
Author(s):  
Gopal Krishna
Keyword(s):  
Data Mining ◽  
Social Networks ◽  
Data Analysis ◽  
Social Networking ◽  
Data Interpretation ◽  
Product Reviews ◽  
Huge Amount ◽  
Data Mining Techniques ◽  
Business Interests ◽  
Contents Sharing

Social networks have drawn remarkable attention from IT professionals and researchers in data sciences. They are the most popular medium for social interaction. Online social networking (OSN) can be defined as involving networking for fun, business, and communication. Social networks have emerged as universally accepted communication means and boomed in turning this world into a global town. OSN media are generally known for broadcasting information, activities posting, contents sharing, product reviews, online pictures sharing, professional profiling, advertisements and ideas/opinion/sentiment expression, or some other stuff based on business interests. For the analysis of the huge amount of data, data mining techniques are used for identifying the relevant knowledge from the huge amount of data that includes detecting trends, patterns, and rules. Data mining techniques, machine learning, and statistical modeling are used to retrieve the information. For the analysis of the data, three methods are used: data pre-processing, data analysis, and data interpretation.

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