CFD_mine : discovery of conditional functional dependencies in relational databases

مقدم أطروحة جامعية

Hakawati, Muhammad Raghib Muhammad

مشرف أطروحة جامعية

Aqil, Misbah Jumah

أعضاء اللجنة

Shilbayah, Nidal
al-Atum, Jalal
Mamluk, Rustum

الجامعة

جامعة الشرق الأوسط

الكلية

كلية تكنولوجيا المعلومات

القسم الأكاديمي

قسم علم الحاسوب

دولة الجامعة

الأردن

الدرجة العلمية

ماجستير

تاريخ الدرجة العلمية

2009

الملخص الإنجليزي

Dirty data (i.e.

containing inconsistences, conflict and errors) is a serious problem for many organizations leading to incorrect decision making, inefficient daily operations, and ultimately wasting both time and money.

Dirty data in a database often emerge as violation of integrity constraints, meant to preserve data consistency and accuracy.

Conditional Functional Dependencies (CFDs) have recently been introduced for data cleaning.

CFDs extends Functional Dependencies (FDs) by enforcing patterns of semantically related values , and have proved more effective in catching data inconsistencies than FDs , which were currently the basis of many data-Cleaning tools Discovery of CFDs existing in an instance of a relation is an expensive process that involves intensive manual effort.

In this thesis, the researcher develops an effective algorithm, called CFD_Mine for discovering CFDs in a relation instance.

CFD_Mine is a Levelwise algorithm that extends TANE, a well-known algorithm for discovering FDs.

it searches for minimal CFDs among the data values and prunes redundant candidates.

An experimental study is presented for showing the scalability of our algorithm .Finally the results show that CFD_Mine works well when a given sample relation is large and scales well will the arity of the relation.

التخصصات الرئيسية

إدارة الأعمال
تكنولوجيا المعلومات وعلم الحاسوب

الموضوعات

• الإدارة
• حماية البيانات
• الخوارزميات
• قواعد البيانات
• الإجراءات الأمنية

عدد الصفحات

54

قائمة المحتويات

• APA
• MLA
• AMA

لغة النص

الإنجليزية

نوع البيانات

رسائل جامعية

رقم السجل

BIM-698627