Integrating data mining with case-based reasoning for chronic diseases prognosis and diagnosis

2007 ◽  
Vol 32 (3) ◽  
pp. 856-867 ◽  
Author(s):  
Mu-Jung Huang ◽  
Mu-Yen Chen ◽  
Show-Chin Lee
Keyword(s):  
Data Mining ◽  
Chronic Diseases ◽  
Case Based Reasoning ◽  
Case Based

Application of Dynamic Data Mining and Case-Based Reasoning in the Drilling Fault Diagnosis

2012 ◽  
Vol 524-527 ◽  
pp. 1350-1354
Author(s):  
Qi Li ◽  
Peng Zhai ◽  
Yun Li Zhao
Keyword(s):  
Data Mining ◽  
Fault Diagnosis ◽  
Knowledge Base ◽  
Case Based Reasoning ◽  
Dynamic Data ◽  
Mining Technology ◽  
Decision Systems ◽  
Static Data ◽  
Fault Diagnosis System ◽  
Case Based

Most of the traditional drilling fault diagnosis & decision systems use static data mining technology, so the update of knowledge base becomes its bottlenecks in its development. In order to meet the actual needs, this paper puts forward the method, which combines dynamic data mining technology with case-based reasoning technology, to design drilling fault diagnosis & decision systems. First, design drilling fault diagnosis system overall, then describe the realization of how to realize dynamic data mining and case-based reasoning in detail, finally, introduce some question about the update of knowledge base.

Customized Recommendation Mechanism Based on Web Data Mining and Case-Based Reasoning

2008 ◽  
pp. 2659-2672
Author(s):  
Jin Sung Kim
Keyword(s):  
Data Mining ◽  
Shopping Mall ◽  
Case Based Reasoning ◽  
Web Data ◽  
Web Data Mining ◽  
Web Based ◽  
Additional Information ◽  
Hybrid Recommendation ◽  
Case Based

One of the attractive topics in the field of Internet business is blending Artificial Intelligence (AI) techniques with the business process. In this research, we suggest a web-based, customized hybrid recommendation mechanism using Case-Based Reasoning (CBR) and web data mining. CBR mechanisms are normally used in problems for which it is difficult to define rules. In web databases, features called attributes are often selected first for mining the association knowledge between related products. Therefore, data mining is used as an efficient mechanism for predicting the relationship between goods, customers’ preference, and future behavior. If there are some goods, however, which are not retrieved by data mining, we can’t recommend additional information or a product. In this case, we can use CBR as a supplementary AI tool to recommend the similar purchase case. Web log data gathered in a real-world Internet shopping mall was given to illustrate the quality of the proposed mechanism. The results showed that the CBR and web data mining-based hybrid recommendation mechanism could reflect both association knowledge and purchase information about our former customers.

Customized Recommendation Mechanism Based on Web Data Mining and Case-Based Reasoning

2004 ◽  
pp. 47-64 ◽  
Author(s):  
Jin Sung Kim
Keyword(s):  
Data Mining ◽  
Shopping Mall ◽  
Case Based Reasoning ◽  
Web Data ◽  
Web Data Mining ◽  
Web Based ◽  
Additional Information ◽  
Hybrid Recommendation ◽  
Case Based

One of the attractive topics in the field of Internet business is blending Artificial Intelligence (AI) techniques with the business process. In this research, we suggest a web-based, customized hybrid recommendation mechanism using Case-Based Reasoning (CBR) and web data mining. CBR mechanisms are normally used in problems for which it is difficult to define rules. In web databases, features called attributes are often selected first for mining the association knowledge between related products. Therefore, data mining is used as an efficient mechanism for predicting the relationship between goods, customers’ preference, and future behavior. If there are some goods, however, which are not retrieved by data mining, we can’t recommend additional information or a product. In this case, we can use CBR as a supplementary AI tool to recommend the similar purchase case. Web log data gathered in a real-world Internet shopping mall was given to illustrate the quality of the proposed mechanism. The results showed that the CBR and web data mining-based hybrid recommendation mechanism could reflect both association knowledge and purchase information about our former customers.

scholarly journals A combined data mining approach using rough set theory and case-based reasoning in medical datasets

2014 ◽  
Vol 3 (3) ◽  
pp. 285-294 ◽  
Author(s):  
Mohammad Taghi Rezvan ◽  
Ali Zeinal Hamadani ◽  
Babak Saffari ◽  
Ali Shalbafzadeh
Keyword(s):  
Data Mining ◽  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Case Based Reasoning ◽  
Data Mining Approach ◽  
Case Based ◽  
Combined Data
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