COURSE UNIT TITLE

: SPATIAL DATA MINING

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
YBS 6018 SPATIAL DATA MINING ELECTIVE 3 0 0 8

Offered By

Management Information Systems

Level of Course Unit

Third Cycle Programmes (Doctorate Degree)

Course Coordinator

PROFESSOR DOCTOR VAHAP TECIM

Offered to

Management Information Systems

Course Objective

This course aims to give students theoretical knowledge about data mining algorithms and techniques, and students to select appropriate data mining techniques for different applications and gain the ability to practice. In this course, students; data preprocessing, association rules analysis, cluster analysis will provide the learning and classification and forecasting applications.

Learning Outcomes of the Course Unit

1   Define basic data mining concepts
2   Apply data preprocessing process
3   Define suitable data mining technique for solving a specific problem
4   Design data mining model
5   Apply data mining algorithm

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction to spatial data mining
2 spatial data mining in further
3 Spatial data preparation (data entegration, reduction, preprocessing and purging and transformation )
4 Sequential spatial data exploration, binding rules and corelations
5 Sequential Spatial Data Analysis
6 Spatial Classification and estimation
7 Spatial Aggregation
8 Case studies
9 Spatial Anomaly acquisition
10 Spatial Data mining tools
11 Web Mining
12 Web Mining
13 Privacy Protection in Spatial Data Mining
14 Presentations

Recomended or Required Reading

Geographic Data Mining and Knowledge Discovery Research Monographs in GIS, Taylor and Francis, 2001.

Planned Learning Activities and Teaching Methods

The activities are detailed in the 'Assessment Methods' and 'Workload Calculation' sections.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 PRJ PROJECT
3 PRS PRESENTATION
4 FIN FINAL EXAM
5 FCG FINAL COURSE GRADE MTE* 0.20 + PRJ* 0.20 + PRS* 0.20 + FIN* 0.40
6 RST RESIT
7 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.20 + PRJ * 0.20 + PRS * 0.20 + RST* 0.40


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

Students' performances are measured with a midterm exam, a project, a presentation and a final exam.

Language of Instruction

Turkish

Course Policies and Rules

The rules applied by the department apply.

Contact Details for the Lecturer(s)

Prof.Dr. Vahap TECIM
vahap.tecim@deu.edu.tr

Office Hours

It will be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 13 3 39
Preparations before/after weekly lectures 13 4 52
Preparation for midterm exam 1 30 30
Preparation for final exam 1 30 30
Preparing presentations 1 10 10
Preparing report 1 27 27
Final 1 1 1
Midterm 1 1 1
TOTAL WORKLOAD (hours) 190

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9
LO.15334
LO.25334
LO.35334
LO.45334
LO.55334

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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