scholarly journals Improving Quality of Educational Processes Providing New Knowledge Using Data Mining Techniques

2014 ◽  
Vol 147 ◽  
pp. 390-397 ◽  
Author(s):  
Manolis Chalaris ◽  
Stefanos Gritzalis ◽  
Manolis Maragoudakis ◽  
Cleo Sgouropoulou ◽  
Anastasios Tsolakidis
Author(s):  
Francisco Javier Villar Martín ◽  
Jose Luis Castillo Sequera ◽  
Miguel Angel Navarro Huerga

The quality of a company's information system is essential and also its physical data model. In this article, the authors apply data mining techniques in order to generate knowledge from the information system's data model, and also to discover and understand hidden patterns within data that regulate the planning of flight hours of pilots and copilots in an airline. With this objective, they use Weka free software which offers a set of algorithms and visualization tools geared to data analysis and predictive modeling of information systems. Firstly, they apply clustering to study the information system and analyze data model; secondly, they apply association rules to discover connection patterns in data; and finally, they generate a decision tree to classify and extract more specific patterns. The authors suggest conclusions according these information system's data to improve future decision making in an airline's flight hours assignments.


Author(s):  
Ibrahiem Mahmoud Mohamed El Emary

This chapter is interested in discussing how to use data mining techniques to assist in achieving an acceptable level of quality of service of telecommunication systems. The quality of service is defined as the metrics which are predicated by using the data mining techniques, decision tree, association rules and neural networks. Routing algorithms can use this metric for optimal path selection which in turn will affect positively on the system performance. Also, in this chapter management axis using data mining techniques were handled, i.e., check the status of the telecommunication networks, role of data mining in obtaining optimal configuration, how to use data mining technique to assure high level of security for the telecommunication. The popularity of data mining in the telecommunications industry can be viewed as an extension of the use of expert systems in the telecommunications industry. These systems were developed to address the complexity associated with maintaining a huge network infrastructure and the need to maximize network reliability while minimizing labor costs (Liebowitz, J. 1988). The problem with these expert systems is that they are expensive to develop because it is both difficult and time consuming to elicit the requisite domain knowledge from experts.


Author(s):  
Jorge Cardoso

Business process management systems (BPMSs) (Smith & Fingar, 2003) provide a fundamental infrastructure to define and manage business processes, Web processes, and workflows. When Web processes and workflows are installed and executed, the management system generates data describing the activities being carried out and is stored in a log. This log of data can be used to discover and extract knowledge about the execution of processes. One piece of important and useful information that can be discovered is related to the prediction of the path that will be followed during the execution of a process. I call this type of discovery path mining. Path mining is vital to algorithms that estimate the quality of service of a process, because they require the prediction of paths. In this work, I present and describe how process path mining can be achieved by using data-mining techniques.


2018 ◽  
Vol 1 (1) ◽  
pp. 35-43
Author(s):  
Ahmed Ashraf ◽  
Hazem El-Bakry ◽  
Yehia Elmashad ◽  
Samir Abd-Elrazik ◽  
Mohammed El-Desouky

Data Mining ◽  
2013 ◽  
pp. 1591-1606
Author(s):  
Ibrahiem Mahmoud Mohamed El Emary

This chapter is interested in discussing how to use data mining techniques to assist in achieving an acceptable level of quality of service of telecommunication systems. The quality of service is defined as the metrics which are predicated by using the data mining techniques, decision tree, association rules and neural networks. Routing algorithms can use this metric for optimal path selection which in turn will affect positively on the system performance. Also, in this chapter management axis using data mining techniques were handled, i.e., check the status of the telecommunication networks, role of data mining in obtaining optimal configuration, how to use data mining technique to assure high level of security for the telecommunication. The popularity of data mining in the telecommunications industry can be viewed as an extension of the use of expert systems in the telecommunications industry. These systems were developed to address the complexity associated with maintaining a huge network infrastructure and the need to maximize network reliability while minimizing labor costs (Liebowitz, J. 1988). The problem with these expert systems is that they are expensive to develop because it is both difficult and time consuming to elicit the requisite domain knowledge from experts.


2020 ◽  
Vol 8 (6) ◽  
pp. 2144-2152

Due to fast advancement in software industry, there was a demand to cut down time and efforts during process of software development. While designing product and services it is very essential to assure quality of product in order to strengthen market value of the product. To accomplish both quality as well as productivity objectives, it is suggested to go for software reuse. Reusability is an essential measure that can be used to improve overall software quality with lesser cost and efforts. This paper gives insights into various literature studies related to software reusability of Object-oriented software using data mining techniques. In this paper even comparative analysis of various techniques related to prediction and enhancement of reusability of Object-Oriented software systems has been done. This would help to get better understanding of need of reusability enhancement of Object-Oriented systems using data mining techniques


2017 ◽  
Vol 13 (2) ◽  
pp. 45-62 ◽  
Author(s):  
Francisco Javier Villar Martín ◽  
Jose Luis Castillo Sequera ◽  
Miguel Angel Navarro Huerga

The quality of a company's information system is essential and also its physical data model. In this article, the authors apply data mining techniques in order to generate knowledge from the information system's data model, and also to discover and understand hidden patterns within data that regulate the planning of flight hours of pilots and copilots in an airline. With this objective, they use Weka free software which offers a set of algorithms and visualization tools geared to data analysis and predictive modeling of information systems. Firstly, they apply clustering to study the information system and analyze data model; secondly, they apply association rules to discover connection patterns in data; and finally, they generate a decision tree to classify and extract more specific patterns. The authors suggest conclusions according these information system's data to improve future decision making in an airline's flight hours assignments.


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