The Department of Defense (DoD) possesses tremendous amounts of data stored in many large databases. Due to the size of these databases, humans are incapable of efficiently discovering interesting and useful patterns so an automated data-mining tool is necessary. Output in the form of production rules, ie., "Ify Then x," is preferred because they are understandable by humans and support decision making processes. This thesis investigates the manner in which data-mining systems discover useful, interesting, but currently unavailable knowledge. The search and evaluation process, guided by a knowledge quality function, is the key task of a data-mining ...
Data-driven knowledge acquisition is one of the key research fields in data mining. Dealingwith larg...
Abstract. In concept learning and data mining tasks, the learner is typically faced with a choice of...
Nowadays, activities and decisions making in an organization is based on data and information obtain...
Large and over the years grown databases are a persistent concern in the field of data quality. Data...
Large and over the years grown databases are a persistent concern in the field of data quality. Data...
Currently, there are many large, automatically constructed knowledge bases (KBs). One interesting ta...
Abstract The quality of discovered association rules is commonly evaluated by interestingness measur...
Knowledge discovery in databases, or data mining, is the process of finding interesting patterns in ...
Knowledge acquisition techniques have been well researched in the data mining community. Such techni...
Every day massive amount of data is generated, collected, and stored in information repositories suc...
Large and over the years grown databases are a persistent concern in the field of data quality. Data...
Every day massive amount of data is generated, collected, and stored in information repositories suc...
Knowledge Discovery in Databases (KDD) is the process of extracting previously unknown, hidden and i...
Knowledge discovery in databases, also known as data mining, is the ecient discovery of previously u...
The development of knowledge engineering and, within its framework, of data mining or knowledge mini...
Data-driven knowledge acquisition is one of the key research fields in data mining. Dealingwith larg...
Abstract. In concept learning and data mining tasks, the learner is typically faced with a choice of...
Nowadays, activities and decisions making in an organization is based on data and information obtain...
Large and over the years grown databases are a persistent concern in the field of data quality. Data...
Large and over the years grown databases are a persistent concern in the field of data quality. Data...
Currently, there are many large, automatically constructed knowledge bases (KBs). One interesting ta...
Abstract The quality of discovered association rules is commonly evaluated by interestingness measur...
Knowledge discovery in databases, or data mining, is the process of finding interesting patterns in ...
Knowledge acquisition techniques have been well researched in the data mining community. Such techni...
Every day massive amount of data is generated, collected, and stored in information repositories suc...
Large and over the years grown databases are a persistent concern in the field of data quality. Data...
Every day massive amount of data is generated, collected, and stored in information repositories suc...
Knowledge Discovery in Databases (KDD) is the process of extracting previously unknown, hidden and i...
Knowledge discovery in databases, also known as data mining, is the ecient discovery of previously u...
The development of knowledge engineering and, within its framework, of data mining or knowledge mini...
Data-driven knowledge acquisition is one of the key research fields in data mining. Dealingwith larg...
Abstract. In concept learning and data mining tasks, the learner is typically faced with a choice of...
Nowadays, activities and decisions making in an organization is based on data and information obtain...