Discovering Quality Knowledge from Relational Databases
نویسنده
چکیده
Current database technology involves processing a large volume of data in order to discover new knowledge. However, knowledge discovery on just the most detailed and recent data does not reveal the long-term trends. Relational databases create new types of problems for knowledge discovery since they are normalized to avoid redundancies and update anomalies, which make them unsuitable for knowledge discovery. A key issue in any discovery system is to ensure the consistency, accuracy, and completeness of the discovered knowledge. We describe the aforementioned problems associated with the quality of the discovered knowledge and provide some solutions to avoid them.
منابع مشابه
Proposing an Improved Semantic and Syntactic Data Quality Mining Method using Clustering and Fuzzy Techniques
Data quality plays an important role in knowledge discovering process in databases. Researchers have proposed two different approaches for data quality evaluation so far. The first approach is based on statistical methods while the second one uses data mining techniques which caused further improvement in data quality evaluation results through relying on knowledge extracting. Our proposed meth...
متن کاملMining Functional Dependency from Relational Databases Using Equivalent Classes and Minimal Cover
Data Mining (DM) represents the process of extracting interesting and previously unknown knowledge from data. This study proposes a new algorithm called FD_Discover for discovering Functional Dependencies (FDs) from databases. This algorithm employs some concepts from relational databases design theory specifically the concepts of equivalences and the minimal cover. It has resulted in large imp...
متن کاملDiscover Dependencies from Data - A Review
Functional and inclusion dependency discovery is important to knowledge discovery, database semantics analysis, database design, and data quality assessment. Motivated by the importance of dependency discovery, this paper reviews the methods for functional dependency, conditional functional dependency, approximate functional dependency and inclusion dependency discovery in relational databases ...
متن کاملDiscovery of Data Dependencies in Relational Databases Lss8 Report 14 Discovery of Data Dependencies in Relational Databases Lss8 Report 14
Knowledge discovery in databases is not only the nontrivial extraction of implicit, previously unknown and potentially useful information from databases. We argue that in contrast to machine learning, knowledge discovery in databases should be applied to real world databases. Since real world databases are known to be very large, they raise problems of the access. Therefore, real world database...
متن کاملDiscovering Association Rules in Incomplete Transactional Databases
The problem of incomplete data in the data mining is well known. In the literature many solutions to deal with missing values in various knowledge discovery tasks were presented and discussed. In the area of association rules the problem was presented mainly in the context of relational data. However, the methods proposed for incomplete relational database can not be easily adapted to incomplet...
متن کامل