[04IN1021] Web Information Retrieval


Dr. Dr. Sergej Sizov
Institute for Web Science and Technologies

The homepage of this lecture can be found here

This course will be offered in two languages: Entirely in English and entirely in Russian. Please specify in your application in which language you prefer to attend the course.


Web Information Retrieval refers to methods and technologies for search, analysis, and automatic organization of data collections: text documents, multimedia contents, structured and semi-structured knowledge representations.  It has quickly become one of the most important areas in Computer and Information Sciences because of its direct applications in e-commerce, e-CRM, corporate knowledge bases and data repositories, Web analytics, and Web information systems.

Recent technological and research trends, such as Linked Open Data and Web Science, are closely related to Information Retrieval and offer new perspectives for data/knowledge organisation and search. The course will introduce mathematical models and algorithms widely used by Web search engines, intranets, and modern digital libraries. We will consider state of the art techniques from linear algebra, statistics, graph mining and machine learning. The course will also provide a brief overview of other areas in Web mining, such as Web content mining and Web structure mining.


Course objectives: deeper understanding of state of the art search/retrieval systems and algorithms, their limitations and recent research/development challenges; ability to design and improve Information Retrieval systems.


Course topics include technical basics (linear algebra, stochastics, graph algorithms, text processing), an overview of common IR methods and models (vector space models, link analysis and authority ranking, multimedia retrieval, organization and ranking of search results) as well as advanced IR topics, such as top-k retrieval, focused crawling, multi-modal analysis of Social Web, and distributed IR.

Required Knowledge

Course requirements: basic knowledge in linear algebra, stochastics and graph algorithms. Recommended prerequisites are courses in data mining and database systems. Assessment of academic achievement: individual oral exam (30 min) at the end of the course.


External students can earn credits per course (3 ECTS for Web Information Retrieval).

Internal diploma students earn credits per course OR have it as part of the oral diploma exam worth 3 ECTS / 2 SWS.

Internal master students in CV and Computer Science earn credit for the module INSS08 "Web Search & Data Mining" (offered by Prof. Dr. York Sure and Dr. Dr. Sergej Sizov), i.e. one joint module for two lectures with integrated exercises, together 6 ECTS = 4 SWS.


Duration / Credits: 2 SWS, 3 ECTS

UNIKO Students: Please register for this course via KLIPS