KDK BASED DOUBLE-BASIS FUSION MECHANISM AND ITS PROCESS MODEL

2005 ◽  
Vol 14 (03) ◽  
pp. 399-423 ◽  
Author(s):  
BINGRU YANG ◽  
JIANGTAO SHEN ◽  
WEI SONG
Keyword(s):  
Knowledge Base ◽  
Knowledge Discovery ◽  
Process Model ◽  
Discovery Process ◽  
New Horizons ◽  
Mining Algorithm ◽  
New Process ◽  
Knowledge Discovery In Database

Knowledge Discovery in Knowledge Base (KDK) opens new horizons for research. KDK and KDD (Knowledge Discovery in Database) are the different cognitive field and discovery process. In most people's view, they are independent each other. In this paper we can summarize the following tasks: Firstly, we discussed that two kinds of the process model and mining algorithm of KDK based on facts and rules in knowledge base. Secondly, we proves that the inherent relation between KDD and KDK (i.e. double-basis fusion mechanism). Thirdly, we gained the new process model and implementation technology of KDK*. Finally, the imitation experimentation proved that the validity of above mechanism and process model.

Knowledge Discovery Process Models

2012 ◽  
pp. 72-100 ◽  
Author(s):  
Mouhib Alnoukari ◽  
Asim El Sheikh
Keyword(s):  
Life Cycle ◽  
Knowledge Discovery ◽  
Process Model ◽  
Common Factor ◽  
Final Outcome ◽  
Process Models ◽  
Data Driven ◽  
Discovery Process ◽  
The Common ◽  
Discovery Process Models

Knowledge Discovery (KD) process model was first discussed in 1989. Different models were suggested starting with Fayyad’s et al (1996) process model. The common factor of all data-driven discovery process is that knowledge is the final outcome of this process. In this chapter, the authors will analyze most of the KD process models suggested in the literature. The chapter will have a detailed discussion on the KD process models that have innovative life cycle steps. It will propose a categorization of the existing KD models. The chapter deeply analyzes the strengths and weaknesses of the leading KD process models, with the supported commercial systems and reported applications, and their matrix characteristics.

Analisis Data Pembayaran Kredit Nasabah Bank Menggunakan Metode Data Mining

2013 ◽  
Vol 4 (1) ◽  
pp. 18-27
Author(s):  
Ira Melissa ◽  
Raymond S. Oetama
Keyword(s):  
Data Mining ◽  
Knowledge Discovery ◽  
Knowledge Discovery In Database

Data mining adalah analisis atau pengamatan terhadap kumpulan data yang besar dengan tujuan untuk menemukan hubungan tak terduga dan untuk meringkas data dengan cara yang lebih mudah dimengerti dan bermanfaat bagi pemilik data. Data mining merupakan proses inti dalam Knowledge Discovery in Database (KDD). Metode data mining digunakan untuk menganalisis data pembayaran kredit peminjam pembayaran kredit. Berdasarkan pola pembayaran kredit peminjam yang dihasilkan, dapat dilihat parameter-parameter kredit yang memiliki keterkaitan dan paling berpengaruh terhadap pembayaran angsuran kredit. Kata kunci—data mining, outlier, multikolonieritas, Anova

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