Searching the Web and Multimedia Databases

The course is not on the list Without time-table
Code Completion Credits Range Language
BI-VWM Z,ZK 5 2P+1C Czech
Department of Software Engineering

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 shall understand the techniques for retrieving text and hypertext documents (the web pages). Moreover, they shall be aware of similarity retrieval methods focused on heterogenous multimedia databases (unstructured data collections, respectively).


Basic knowledge and skills in algorithmics, programming, data structures and database technologies.

Syllabus of lectures:

1. Web space, search engines, web retrieval modalities.

2. Boolean model of information retrieval.

3. Vector model of information retrieval.

4. Link analysis and the web page ranking.

5. Search engine optimization.

6. Semantic web.

7. Introduction to the similarity search in multimedia databases.

8. Similarity queries, aggregation operators.

9. Indexing metric similarity for efficient multimedia retrieval.

10. Approximate similarity retrieval.

11. Advanced similarity search models.

Syllabus of tutorials:

1. Project topic presentation.

2. Group consultations.

3. Group consultations.

4. Individual consultations.

5. Individual consultations.

6. Project presentation.

7. Project presentation.

Study Objective:

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:

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

Further information:
No time-table has been prepared for this course
The course is a part of the following study plans:
Data valid to 2020-10-20
For updated information see http://bilakniha.cvut.cz/en/predmet1123906.html