Searching Web and Multimedia Databases
Code | Completion | Credits | Range | Language |
---|---|---|---|---|
BIE-VWM | Z,ZK | 5 | 2P+1C | English |
- Course guarantor:
- Lecturer:
- Tutor:
- Supervisor:
- Department of Software Engineering
- Synopsis:
-
Students gain basic knowledge concerning retrieval techniques on the web, where the web environment is viewed as a large distributed and heterogenous data repository. In particular, the students will understand the techniques for retrieving text and hypertext documents (the web pages). Moreover, they will be aware of similarity retrieval methods focused on heterogenous multimedia databases (unstructured data collections, respectively).
- Requirements:
-
Basic knowledge and skills in algorithmics, programming, data structures and database technologies.
- Syllabus of lectures:
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1. Web space, search engines, web retrieval modalities.
2. Boolean model of information retrieval.
3. Vector model of information retrieval.
4. Link analysis and PageRank.
5. Web page ranking and search engine optimization.
6. Semantic web and Linked data.
7. Deep web and social context.
8. Introduction to the similarity search in multimedia databases.
9. Similarity queries.
10. Indexing metric similarity for efficient multimedia retrieval.
11. Approximate similarity retrieval.
12. Advanced similarity search models.
- Syllabus of tutorials:
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1. Project topic presentation.
2. Group consultations.
3. Group consultations.
4. Individual consultations.
5. Individual consultations.
6. Project presentation.
7. Project presentation.
- Study Objective:
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This module is recommended for students that are interested in deeper understanding of web search engines. In particular, text, hypertext, and multimedia retrieval techniques are explored. The retrieval techniques are described in three layers: theoretical (model), algorithmical, and application. Then, in experimental projects, the students can implement the methods and employ them in various web applications.
- Study materials:
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course slides +
1) Ricardo Baeza-Yates, Berthier Ribeiro-Neto. Modern Information Retrieval: The Concepts and Technology behind Search, 2011, Addison-Wesley Professional, ISBN-10: 0321416910
2) Amy N. Langville, Carl D. Meyer. Google's PageRank and Beyond: The Science of Search Engine Rankings, 2012, Princeton University Press, ISBN-10: 0691152667
3) Kristopher B. Jones. Search Engine Optimization: Your Visual Blueprint for Effective Internet Marketing, 2013, Visual, ISBN-10: 1118551745
4) Pavel Zezula, Giuseppe Amato, Vlastislav Dohnal, Michal Batko. Similarity Search: The Metric Space Approach, 2005, Springer, ISBN-10: 0387291466
5) Charu C. Aggarwal. Data Mining: The Textbook. 2015, Springer, ISBN-10: 9783319141411
- Note:
- Further information:
- https://courses.fit.cvut.cz/BI-VWM/
- No time-table has been prepared for this course
- The course is a part of the following study plans:
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- Bachelor branch Security and Information Technology, in English, 2015-2020 (elective course)
- Bachelor branch Web and Software Engineering, spec. Software Engineering, in English, 2015-2020 (elective course)
- Bachelor branch Computer Science, in English, 2015-2020 (elective course)
- Bachelor branch Computer Science, in English, 2015-2020 original version (elective course)