A new approach for mining functional dependency from relational databases

Dissertant

Badr, Dojanah Muhammad Kadri

Thesis advisor

al-Atum, Jalal Umar

Comitee Members

Kanan, Ghassan Jaddu
al-Shalabi, Riyad
Abu al-Suud, Salih Mustafa

University

Arab Academy for Financial and Banking Sciences

Faculty

The Faculty of Information Systems and Technology

Department

Computer information systems

University Country

Jordan

Degree

Ph.D.

Degree Date

2008

English Abstract

Data Mining (DM) represents the process of extracting interesting and previously unknown knowledge from data.

In this thesis we address the important data mining problem of discovering functional dependencies from databases.

DM or knowledge discovery from databases have been attracting a ignificant amount of research.

This thesis provides an overview of this emerging field, clarifying how data mining and knowledge discovery in databases are related both to each other and to related fields, such as machine learning, statistics, and databases.

This thesis mentions particular real world applications, specific data mining techniques, challenges involved in real world applications of knowledge discovery, and current and future research directions in the field.

This thesis proposed a new algorithm called FD_Discover for Discovering Functional Dependencies (FDs) from databases.

This algorithm employs some concepts from relational databases design theory as the concept of equivalences and the concept of minimal cover.

This new algorithm has resulted in large improvement in performance in comparison with a recent and similar algorithm called FD_MINE.

Main Subjects

Information Technology and Computer Science

Topics

• Data processing
• Databases
• Relational databases
• Data mining

No. of Pages

72

Table of Contents

• APA
• MLA
• AMA

Language

English

Data Type

Arab Theses

Record ID

BIM-306380