Improvement Assessment Method for Special Kids By Observing The Social and Behaviour Activity Using Data Mining Techniques

2021 ◽  
Vol 1 (1) ◽  
pp. 1
Author(s):  
DHANALAKSHMI RADHAKRISHNAN ◽  
Muthukumar B
Keyword(s):  
Data Mining ◽  
Assessment Method ◽  
Data Mining Techniques ◽  
The Social ◽  
Using Data ◽  
Improvement Assessment

scholarly journals Mining on Social Media Data: To Determine the Personality of Unrevealed Person

2019 ◽  
Vol 8 (4) ◽  
pp. 8574-8577
Keyword(s):  
Data Mining ◽  
Social Media ◽  
Information Mining ◽  
Social Media Data ◽  
Data Mining Techniques ◽  
Network Discovery ◽  
The Social ◽  
Mining Methods ◽  
Using Data ◽  
Media Data

The unavoidable utilization of online networking like Facebook is giving exceptional measures of social information. Information mining methods have been broadly used to separate learning from such information. The character of the person is predicted whether he is good or not by using data mining techniques from user self-made data. Mining methods are being broadly using to separate learning from such information, main examples for them are network discovery and slant investigation. Notwithstanding, there is still a lot of room to investigate as far as the occasion information (i.e., occasions with timestamps, for example, posting an inquiry, altering an article in Wikipedia, and remarking on a tweet. These occasions react users' personal conduct standards and working forms in the social media websites.

A Conceptual Framework for Social Network Data Security

2013 ◽  
pp. 58-86 ◽  
Author(s):  
Sanur Sharma ◽  
Vishal Bhatnagar
Keyword(s):  
Data Mining ◽  
Social Network ◽  
Conceptual Framework ◽  
Social Networking Sites ◽  
Community Analysis ◽  
Network Data ◽  
Data Mining Techniques ◽  
Social Network Data ◽  
The Social ◽  
Using Data

In recent times, there has been a tremendous increase in the number of social networking sites and their users. With the amount of information posted on the public forums, it becomes essential for the service providers to maintain the privacy of an individual. Anonymization as a technique to secure social network data has gained popularity, but there are challenges in implementing it effectively. In this chapter, the authors have presented a conceptual framework to secure the social network data effectively by using data mining techniques to perform in-depth social network analysis before carrying out the actual anonymization process. The authors’ framework in the first step defines the role of community analysis in social network and its various features and temporal metrics. In the next step, the authors propose the application of those data mining techniques that can deal with the dynamic nature of social network and discover important attributes of the social network. Finally, the authors map their security requirements and their findings of the network properties which provide an appropriate base for selection and application of the anonymization technique to protect privacy of social network data.

IDENTIFICATION OF CRITICAL INFRASTRUCTURE USING DATA MINING TECHNIQUES

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Su-Ling Fan ◽  
Chang-Saar Chai ◽  
Kumar Vikram
Keyword(s):  
Data Mining ◽  
Continuous Flow ◽  
Critical Infrastructure ◽  
Economic Factors ◽  
Data Mining Techniques ◽  
The Social ◽  
Using Data ◽  
Disaster Protection ◽  
The Relationship

Critical Infrastructure (CI) is a term used to describe important national assets for producing or distributing a continuous flow of essential goods or services. They are marked by immense complexity, characterized predominantly by strong intra and interdependencies as well as hierarchies. These interconnections take many forms, including flows of information, shared security, physical flows of commodities, and others. Previous research has illustrated the relationship between the physical impacts of natural disasters and the social and economic factors on CI. Some research emphasized more the role of CI interdependencies and their importance and influence over the functioning of industries while others have looked the impacts due to disruption of CI after disasters. Nowadays comprehensive identification of all interdependency relationships of CI remains a challenge. As the complexity and interconnectedness of a country's CI evolve, threats and vulnerabilities increase. Thus, investigating how a set of CI interacts and identification of criticality of CI becomes an important topic. This research has made utilization of data mining techniques and proposes a method to identify the criticality of Critical Infrastructure so that to develop better disaster protection and prevention management.

Analysis of Crop Yield Prediction of Kharif & Rabi Jowar Crops Using Data Mining Techniques

2017 ◽  
Vol 7 (11) ◽  
pp. 79
Author(s):  
Sujata Mulik
Keyword(s):  
Data Mining ◽  
Crop Yield ◽  
Crop Production ◽  
Climatic Factors ◽  
Crop Productivity ◽  
Yield Prediction ◽  
Data Mining Techniques ◽  
Agriculture Sector ◽  
Using Data ◽  
Rabi Crops

Agriculture sector in India is facing rigorous problem to maximize crop productivity. More than 60 percent of the crop still depends on climatic factors like rainfall, temperature, humidity. This paper discusses the use of various Data Mining applications in agriculture sector. Data Mining is used to solve various problems in agriculture sector. It can be used it to solve yield prediction.  The problem of yield prediction is a major problem that remains to be solved based on available data. Data mining techniques are the better choices for this purpose. Different Data Mining techniques are used and evaluated in agriculture for estimating the future year's crop production. In this paper we have focused on predicting crop yield productivity of kharif & Rabi Crops. 

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