The ideal situation for a Data Mining or Knowledge Discovery system would be for the user to be able to pose a query of the form "Give me something interesting that could be useful" and for the system to discover some useful knowledge for the user. But such a system would be unrealistic as databases in the real world are very large and so it would be too inefficient to be workable. So the role of the human within the discovery process is essential. Moreover, the measure of what is meant by "interesting to the user" is dependent on the user as well as the domain within which the Data Mining system is being used. In this paper we discuss the use of domain knowledge within Data Mining. We define three classes of domain know...
Knowledge Discovery in Databases (KDD) is the process of extracting previously unknown, hidden and i...
Every day massive amount of data is generated, collected, and stored in information repositories suc...
Data mining (knowledge discovery from data) may be viewed as the extraction of interesting (non-triv...
The mainstream data mining faces critical challenges and lacks of soft power in solving real-world c...
In recent years both the number and the size of organisational databases have increased rapidly. How...
In recent years both the number and the size of organisational databases have increased rapidly. How...
Knowledge discovery in databases, or data mining, is an important issue in the development of data- ...
Abstract Web data mining tends to be characterized as the most common way of getting concealed data...
This study investigates an approach of knowledge discovery and data mining in insufficient databases...
Knowledge discovery in databases, also known as data mining, is the ecient discovery of previously u...
Every day massive amount of data is generated, collected, and stored in information repositories suc...
In this chapter, data mining and knowledge discovery (DMKD) is presented with basic concepts, a brie...
Traditional data mining research mainly focus]es on developing, demonstrating, and pushing the use o...
Data Mining and Knowledge Discovery is a tested companion investigated logical diary zeroing in on d...
Abstract: The Knowledge Discovery in Databases and Data Mining field proposes the development of met...
Knowledge Discovery in Databases (KDD) is the process of extracting previously unknown, hidden and i...
Every day massive amount of data is generated, collected, and stored in information repositories suc...
Data mining (knowledge discovery from data) may be viewed as the extraction of interesting (non-triv...
The mainstream data mining faces critical challenges and lacks of soft power in solving real-world c...
In recent years both the number and the size of organisational databases have increased rapidly. How...
In recent years both the number and the size of organisational databases have increased rapidly. How...
Knowledge discovery in databases, or data mining, is an important issue in the development of data- ...
Abstract Web data mining tends to be characterized as the most common way of getting concealed data...
This study investigates an approach of knowledge discovery and data mining in insufficient databases...
Knowledge discovery in databases, also known as data mining, is the ecient discovery of previously u...
Every day massive amount of data is generated, collected, and stored in information repositories suc...
In this chapter, data mining and knowledge discovery (DMKD) is presented with basic concepts, a brie...
Traditional data mining research mainly focus]es on developing, demonstrating, and pushing the use o...
Data Mining and Knowledge Discovery is a tested companion investigated logical diary zeroing in on d...
Abstract: The Knowledge Discovery in Databases and Data Mining field proposes the development of met...
Knowledge Discovery in Databases (KDD) is the process of extracting previously unknown, hidden and i...
Every day massive amount of data is generated, collected, and stored in information repositories suc...
Data mining (knowledge discovery from data) may be viewed as the extraction of interesting (non-triv...