scholarly journals AN INDISCERNIBILITY APPROACH FOR PRE PROCESSING OF WEB LOG FILES

2012 ◽  
pp. 231-234
Author(s):  
JEEVA JOSE ◽  
P. SOJAN LAL
Keyword(s):  
World Wide Web ◽  
Set Theory ◽  
Rough Set ◽  
World Wide ◽  
Rough Set Theory ◽  
Web Usage Mining ◽  
Web Log ◽  
Log Files ◽  
Challenging Tasks ◽  
And Behavior

World Wide Web has a spectacular growth not only in terms of the number of websites and volume of information, but also in terms of the number of visitors. Web log files contain tremendous information about the user traffic and behavior. A large amount of pre processing is required for eliminating the noise and is one of the challenging tasks in web usage mining. This paper proposes an indiscernibility approach in rough set theory for pre processing of web log files.

scholarly journals Prediction of Student Performance Using Rough Set Theory And Backpropagation Neural Networks

2021 ◽  
Vol 17 (7) ◽  
Author(s):  
Bruno Cristos Madeira ◽  
Tugrul Tasci ◽  
Numan Celebi
Keyword(s):  
Neural Network ◽  
Student Performance ◽  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Educational Data Mining ◽  
Web Based ◽  
Original Dataset ◽  
The Neural Network ◽  
And Behavior

With the rise of web-based education systems and the increased use of information systems in education institutions, the amount of data recorded on student performance and behavior has increased exponentially. Thus, bringing about a large number of contributions to the field of educational research, which in itself contributed to the further evolution off the field in the last two decades alone, with terms such as Educational Data Mining (EDM), Learning Analytics, Data-driven Education, Teaching Analytics and others being added to the literature. In this paper, we evaluate the usefulness of a model using Rough Set Theory (RST) and Backpropagation Neural Network (BPNN) in effectively predicting the students’ overall performance. The dataset used consists of 10 different attributes and one decision factor belonging to 53 students collected from a language course which administers in-person education with the aid of an online platform for assignments. RST was implemented in order to reduce the number of attributes used as input in the neural network and the BPNN made an accurate prediction using only 5 of the initial attributes. Thus outperforming a model based solely on BPNN used on the original dataset and reducing computational costs.

A rough set theory application in forecasting models

2020 ◽  
Vol 3 (2) ◽  
pp. 1-21 ◽  
Author(s):  
Haresh Sharma ◽  
◽  
Kriti Kumari ◽  
Samarjit Kar ◽  
◽  
...  
Keyword(s):  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Forecasting Models ◽  
Theory Application

Extraction of Geo-spatial Relationship Rules Based on Rough Set Theory: Exemplified by Land Use

2009 ◽  
Vol 11 (2) ◽  
pp. 139-144
Author(s):  
Feng CAO ◽  
Yunyan DU ◽  
Yong GE ◽  
Deyu LI ◽  
Wei WEN
Keyword(s):  
Land Use ◽  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Spatial Relationship

Analysing diabetes using rough sets

2020 ◽  
pp. 533-538
Author(s):  
S. Arjun Raj ◽  
M. Vigneshwaran
Keyword(s):  
Set Theory ◽  
Rough Set ◽  
Rough Sets ◽  
Rough Set Theory ◽  
International Diabetes Federation ◽  
Published Data ◽  
Lower And Upper Approximations

In this article we use the rough set theory to generate the set of decision concepts in order to solve a medical problem.Based on officially published data by International Diabetes Federation (IDF), rough sets have been used to diagnose Diabetes.The lower and upper approximations of decision concepts and their boundary regions have been formulated here.

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