PA128 Similarity Searching in Multimedia Data

Faculty of Informatics
Spring 2024
Extent and Intensity
2/0/0. 2 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Taught in person.
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
Mon 10:00–11:50 A319
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.
  • 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.
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
Further Comments
Study Materials
The course is taught annually.
Listed among pre-requisites of other courses
The course is also listed under the following terms Spring 2003, Spring 2004, Spring 2005, Spring 2006, Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Spring 2025.
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