Παρουσίαση/Προβολή

Instructors

Georgios Evangelidis (gevan@uom.edu.gr)
Georgia Koloniari (gkoloniari@uom.edu.gr)

Course Syllabus

Knowledge Discovery in Databases Concepts

Exploratory Data Analysis and Visualization

Data Reduction

Classification

Clustering

Association Rules

Introduction to Web Mining

Link Analysis

Graph Mining

Web Usage Mining

Recommender Systems

Course Objectives/Goals

Upon completion of the course, the student will be able to:
(a) understand the concept of knowledge discovery from databases;
(b) understand the value of exploratory data analysis and visualization as a preprocessing step;
(c) understand and apply data reduction techniques;
(d) understand and apply knowledge mining techniques from data such as classification, clustering, association rules using common tools (e.g., WEKA, R, Python);
(e) understand and apply knowledge mining techniques on the World Wide Web.

Prerequisites/Prior Knowledge

Databases, Programming

Bibliography

• P.-N. Tan, M. Steinbach, A. Karpatne and V. Kumar, Introduction to Data Mining, 2nd Edition, Addison Wesley, 2018.
• J. Leskovec, A. Rajaraman and J.D. Ullman, Mining of Massive Datasets, 3rd Edition, Cambridge University Press, 2020.
• Mohammed J. Zaki, Wagner Meira Jr., Data Mining and Analysis: Fundamental Concepts and Algorithms, Cambridge University Press, 2014.

Assessment Methods

- Written examination at the end of the semester including problem solving, multiple choice test and short answer questions (50%)

- Homework assignments (20%)
- Compulsory code development assignments (30%)

To participate in the final exam a student must have submitted the code development assignments. 

Calculation of final grade:

The final grade is derived by 50% from the grade of the final written exam (scale 0 - 10) and by 50% from the grade of the additional assessment methods (scale 0 - 10), only in the case that the grade of the final exam is passing (>=5). Otherwise, the final grade is equal to the 50% of the final exam. 

If a student has not submitted the code development assignments by the exams in January/February, they can submit them until the September exams and participate in those.

Instructional Methods

Weekly lectures