Loading...
Please wait, while we are loading the content...
Knowledge discovery and data mining (kdd-2003).
| Content Provider | CiteSeerX |
|---|---|
| Abstract | Multi-Relational Data Mining (MRDM) is the multi-disciplinary field dealing with knowledge discovery from relational databases consisting of multiple tables. Mining data which consists of complex/structured objects also falls within the scope of this field, since the normalized representation of such objects in a relational database requires multiple tables. The field aims at integrating results from existing fields such as inductive logic programming, KDD, machine learning and relational databases; producing new techniques for mining multi-relational data; and practical applications of such tecniques. Typical data mining approaches look for patterns in a single relation of a database. For many applications, squeezing data from multiple relations into a single table requires much thought and effort and can lead to loss of information. An alternative for these applications is to use multi-relational data mining. Multi-relational data mining can analyze data from a multi-relation database directly, without the need to transfer the data into a single table first. Thus the relations mined can reside in a relational or deductive database. Using multirelational |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Single Relation Multi-relational Data Knowledge Discovery Data Mining Multiple Table Typical Data Mining Approach Inductive Logic Programming Machine Learning Single Table Many Application Complex Structured Object Normalized Representation Practical Application Multiple Relation Multi-relation Database Multi-relational Data Mining Relational Database Deductive Database Mining Data New Technique Multi-disciplinary Field |
| Content Type | Text |
