scholarly journals Subgroup discovery: on-line data mining server and its application

Author(s):  
D. Gamberger
1998 ◽  
Vol 11 (5-6) ◽  
pp. 331-338 ◽  
Author(s):  
Robert Milne ◽  
Mike Drummond ◽  
Patrick Renoux
Keyword(s):  
On Line ◽  

Author(s):  
Jose Alberto ◽  
Crispin Zavala ◽  
Ocotlan Diaz ◽  
Gennadiy Burlak ◽  
Alberto Ochoa ◽  
...  

Author(s):  
Anastasia Y. Nikitaeva

This chapter substantiates the importance of improving management effectiveness of mesoeconomic systems in current economic conditions and the features of mesoeconomy as a management object which defines the high complexity of decision making at the meso level. There are approaches, methods, and technologies which provide support of the decision making process via the integration of formal methods for objective data analysis and methods of accounting to solve semi-structured complex problems of mesoeconomy. A cognitive approach, and an approach involving the integration of the On-Line Analytical Processing and Data mining technologies with methods of a multi-criteria assessment of alternative, in particular methods of Multi-Attribute Utility Theory are considered in the chapter. Cognitive mapping of interaction between state and business in a mesoeconomic system are included as a case-study.


In today era credit card are extensively used for day to day business as well as other transactions. Ascent within the variety of transactions through master card has junction rectifier to rise in the dishonest activities. In trendy day's fraud is one in every of the most important concern within the monetary loses not solely to the merchants however additionally to the individual purchasers. Data processing had competed a commanding role within the detection of credit card in on-line group action. Our aim is to first of all establish the categories of the fraud secondly, the techniques like K-nearest neighbor, Hidden Markov model, SVM, logistic regression, decision tree and neural network. So fraud detection systems became essential for the banks to attenuate their loses. In this paper we have research about the various detecting techniques to identify and detect the fraud through varied techniques of data mining


DM techniques DM techniques give helpful info from the historical comes counting on that the hiring-manager will build selections for recruiting high-quality force, by applying K-means and mathematical logic algorithms. huge information analytics in hiring and the way it will assist you recruit prime talent, "Big information is that the way forward for recruiting, however you cannot simply information mine your thanks to the privilege candidate, “Big info to alter your accomplishment system. What’s certain is that big info is that the fate of occupation choosing and advancement, Associate in Nursing seeing a way to know it are going to be basic to an organization's prosperity. Nowadays, vast info helps quickly developing organizations find their ideal specialists, designers and officers. an enormous information platform utilizing prophetic analytics and machine learning for quick, accurate, and straightforward candidate rummage around for recruiters. During this paper a data-mining framework supported Associate in nursing ensemble-learning technique to refocus on the factors for personnel. On-line job boards are employed by scores of job seekers, UN agency flick through the postings for jobs that match their interest. Queries are crafted victimization word generated by the users, which cannot match the language employed in the work postings.


2019 ◽  
Vol 16 (2) ◽  
pp. 573-575
Author(s):  
Jafar Ali S. Ibrahim ◽  
M. Thangamani

Healthcare providers need to be up-to-date with all new discoveries about a certain treatment, in order to identify if it might have side effects for certain types of patients. It envisions the potential and value of the findings of our work as guidelines for the performance of a framework that is capable to find relevant information about diseases and treatments in a medical domain repository. This research identifies the disease name with the symptoms specified and extract the sentence from the article and get the relation that exists between disease-treatment and classifies the information into the cure, prevents any side effect to the user. It demonstrates the disease treatment interaction through the online form without going to the doctor.


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