Advanced Topics in Databases
| Title | Προχωρημένα Θέματα Βάσεων Δεδομένων / Advanced Topics in Databases |
| Code | DWS206 |
| Faculty | Sciences |
| School | Informatics |
| Cycle / Level | 2nd / Postgraduate |
| Teaching Period | Spring |
| Coordinator | Eleftherios Tiakas |
| Common | Yes |
| Status | Active |
| Course ID | 600016265 |
Programme of Study: PMS EPISTĪMĪ DEDOMENŌN KAI PAGKOSMIOU ISTOU (2018 éōs sīmera) PF
Registered students: 7
| Orientation | Attendance Type | Semester | Year | ECTS |
|---|---|---|---|---|
| KORMOS | Elective Courses belonging to the selected specialization | 2 | 1 | 7.5 |
| Academic Year | 2018 – 2019 |
| Class Period | Spring |
| Instructors from Other Categories |
|
| Weekly Hours | 3 |
| Total Hours | 39 |
| Class ID | 600132040
|
Course Type 2011-2015
Specific Foundation / Core
Mode of Delivery
- Face to face
Digital Course Content
- e-Study Guide https://qa.auth.gr/en/class/1/600132040
- eLearning (Moodle): https://elearning.auth.gr/course/view.php?id=11632
Prerequisites
General Prerequisites
There is no list of prerequisite courses in the strict sense. Students should master topics related to Databases, Programming with Java and C++ and Data Mining.
Learning Outcomes
After the course completion students will have a concrete view of the methods used for spatial and multimedia data mamagement. Moreover, they will be able to apply indexing schemes (as well as other methods) in multimedia data. In addition, the assignments will help students to gain additional knowledge and solve practical problems.
General Competences
- Apply knowledge in practice
- Make decisions
- Work autonomously
- Generate new research ideas
Course Content (Syllabus)
Spatial and Multimedia Databases with emphasis on high dimensional data, Spatial Data Models, Spatial Query Languages, Spatial Storage and Indexing, Spatial Query Processing Algorithms and Optimization, Spatial Networks, Information Retrieval, Content-based Information Systems, Multidimensional Indexing Techniques, B-Trees and their variants, persistent trees, buffer trees, R-Trees and their variants, X-Trees, M-Trees, Slim-Trees, Similarity Query Processing Algorithms in Multidimensional Spaces, Similarity Query Processing Algorithms in Metric Spaces, Preference Queries (top-k, skylines), hash indexing techniques.
Keywords
Spatial and Multimedia Databases, Indexing methods, Query Processing, Top-k, Skyline
Educational Material Types
- Notes
- Slide presentations
- Book
Use of Information and Communication Technologies
Use of ICT
- Use of ICT in Course Teaching
- Use of ICT in Laboratory Teaching
- Use of ICT in Communication with Students
Course Organization
| Activities | Workload | ECTS | Individual | Teamwork | Erasmus |
|---|---|---|---|---|---|
| Lectures | 39 | ✓ | |||
| Reading Assigment | 100 | ✓ | |||
| Project | 55 | ✓ | ✓ | ||
| Written assigments | 32 | ✓ | |||
| Total | 226 |
Student Assessment
Description
Students grades are based on: (a) written examination (50%), and (b) development of a system related to spatial/multimedia data management, submission of a report an presentation of the system in class (50%).
Bibliography
Additional bibliography for study
S. Shekhar, S. Chawla: Spatial Databases: A Tour, Prentice Hall, 2003.
P. Rigaux, M. Scholl, A. Voisard: Spatial Databases: With Application to GIS, Morgan Kaufmann, 2001.
H. Samet: Foundations of Multidimensional and Metric Data Structures, Morgan Kaufmann, 2006.
R. H. Guting, M. Schneider, Moving Objects Databases, Morgan Kaufmann, 2005.
A. Baughman, J. Gao, J.-Y. Pan, V.A. Petrushin (eds): Multimedia Data Mining and Analytics: Disruptive Innovation, Springer, 2015.
K. S. Candan, M. L.Sapino, Data Management for Multimedia Retrieval, Cambridge University Press, 2010.
O. Marques, B. Furht: Content-Based Image and Video Retrieval, Springer, 2002.
P. Muneesawang, N. Zhang, L. Guan: Multimedia Database Retrieval: Technology and Applications, Springer, 2014.
L. Liu, M. T. Ozsu (eds): Encyclopedia of Database Systems, Springer, 2009.
J. Vitter, Algorithms and Data Structures for External Memory, 2008.
J. Abello, P.M. Pardalos and M.G.C. Resende (editors), Handbook of Massive Data Sets, Kluwer Academic Publishers, 2002.
D. Menta and S Sahni, Handbook of Data Structures and Application. 2005.
Last Update
28-01-2020
