Web Data Mining

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Code	Completion	Credits	Range	Language
MIE-DDW	Z,ZK	4	2P+1C	English

Course guarantor:

Lecturer:

Tutor:

Supervisor:

Department of Software Engineering

Synopsis:

A student learns in detail about various search and data mining methods and will be able to select, in the context of a given application, a suitable method of automatic web data processing and to control the process of its usage.

Requirements:

Familiarity with basic principles of WWW data representation, such as the HTML language.

Syllabus of lectures:

1. Main topic of the web mining: Web Content Mining, Web Structure Mining, and Web Usage Mining.

2. An overview of practical web mining applications.

3. Web Content Mining: document indexing and retrieval in the web environment, Boolean and vector retrieval models, latent semantic indexing (LSI), results ordering, meta-search.

4. Web Content Mining: web documents categorization and clustering.

5. Natural Language Processing methods used for web information retrieval: lemmatization, part-of-speech tagging, disambiguation, shallow syntactic parsing, etc.

6. Web Structure Mining: primary web browsing (crawling, spidering), link topology analysis, PageRank, HITS methods.

7. Global analysis of the Web; social networks analysis.

8. Web Usage Mining: mining for user behavior on the web, internet marketing.

9. Information Extraction as a specific type of web content mining: wrapper-based vs. token activated extraction.

10. Specific applications: opinion mining vs. fact mining, web spam analysis, comparative shopping, etc.

11. Web information integration, mapping schemas usage.

12. Web Mining and its relation to the Semantic Web: automatic semantic annotation, ontology learning, Semantic Web search.

Syllabus of tutorials:

Study Objective:

Provide students with an overview of web mining technologies and qualify them to use some of them in practice.

Study materials:

1. Chakrabarti, S. ''Mining the Web: Discovering Knowledge from Hypertext Data''. Morgan Kaufmann, 2002. ISBN 1558607544.

2. Konchady, M. ''Building Search Applications: Lucene, LingPipe, and Gate''. Mustru Publishing, 2008. ISBN 0615204252.

Note:

Further information:

https://courses.fit.cvut.cz/MI-DDW/

No time-table has been prepared for this course

The course is a part of the following study plans: