Performance Evaluation of Social Network Using Data Mining Techniques

2012 ◽  
pp. 25-49 ◽  
Author(s):  
Mrutyunjaya Panda ◽  
Ajith Abraham ◽  
Sachidananda Dehuri ◽  
Manas Ranjan Patra
Keyword(s):  
Data Mining ◽  
Performance Evaluation ◽  
Social Network ◽  
Data Mining Techniques ◽  
Using Data

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.

scholarly journals A Survey on Performance Evaluation and Prediction of Teachers’, Students’ Performance Using Data Mining Techniques

IJARCCE ◽  
2017 ◽  
Vol 6 (1) ◽  
pp. 281-285 ◽  
Author(s):  
Sudarshan B. Wadkar ◽  
Dr. Dharmadhikari S. C. ◽  
Santosh Kumar Dwivedi
Keyword(s):  
Data Mining ◽  
Performance Evaluation ◽  
Data Mining Techniques ◽  
Using Data

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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