FI:PA128 Similarity Searching - Course Information
PA128 Similarity Searching in Multimedia Data
Faculty of InformaticsSpring 2023
- Extent and Intensity
- 2/0/0. 2 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
- Teacher(s)
- prof. Ing. Pavel Zezula, CSc. (lecturer)
doc. RNDr. Vlastislav Dohnal, Ph.D. (assistant)
RNDr. Michal Batko, Ph.D. (assistant) - Guaranteed by
- prof. Ing. Pavel Zezula, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: prof. Ing. Pavel Zezula, CSc.
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics - Timetable
- Mon 13. 2. to Mon 15. 5. Mon 10:00–11:50 B410
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- there are 77 fields of study the course is directly associated with, display
- Course objectives
- The objective of the course is to introduce the idea of similarity search on unstructured data and define basic similarity queries and data partitioning principles. Based on these fundamentals, the current state of the art of centralized, approximate, and distributed index structures is presented.
- Learning outcomes
- Upon successful completion of the course student will be able:
to understand principles of similarity searching;
to apply similarity searching paradigm to multimedia data;
to explain principles of index structures for multimedia data;
to implement an index structure introduced in the course. - Syllabus
- Part I Metric Searching in a Nutshell:
- Foundations of Metric Space Searching
- Survey of Existing Approaches
- Part II Metric Searching in Large Collections of Data:
- Centralized Index Structures
- Approximate Similarity Search
- Parallel and Distributed Indexes.
- Literature
- recommended literature
- ZEZULA, Pavel, Giuseppe AMATO, Vlastislav DOHNAL and Michal BATKO. Similarity Search: The Metric Space Approach. 2005th ed. New York, NY 10013, USA: Springer, 2005, 220 pp. Advances in Database Systems, Vol. 32. ISBN 0-387-29146-6. Publisher's page Home page info
- Teaching methods
- Lectures with slides. The course is given in English. Questions during lectures are allowed also in Czech.
- Assessment methods
- Final exams are organized during the examination period and the exam is combined: a short written exam and oral examination. The student is asked two questions to verify the student's knowledge obtained during lectures.
- Language of instruction
- English
- Further Comments
- Study Materials
The course is taught annually. - Listed among pre-requisites of other courses
- Enrolment Statistics (Spring 2023, recent)
- Permalink: https://is.muni.cz/course/fi/spring2023/PA128