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Web Semantization - NSWI108

Title:	Sémantizace webu
Guaranteed by:	Department of Software Engineering (32-KSI)
Faculty:	Faculty of Mathematics and Physics
Actual:	from 2016 to 2018
Semester:	winter
E-Credits:	5
Hours per week, examination:	winter s.:2/2, C+Ex [HT]
Capacity:	unlimited
Min. number of students:	unlimited
4EU+:	no
Virtual mobility / capacity:	no
State of the course:	taught
Language:	Czech, English
Teaching methods:	full-time
Teaching methods:	full-time
Additional information:	http://www.ksi.mff.cuni.cz/~vojtas/vyuka/vyuka.html
Note:	enabled for web enrollment

Guarantor:	prof. RNDr. Peter Vojtáš, DrSc.
Class:	Informatika Mgr. - Softwarové systémy
Classification:	Informatics > Informatics, Software Applications, Computer Graphics and Geometry, Database Systems, Didactics of Informatics, Discrete Mathematics, External Subjects, General Subjects, Computer and Formal Linguistics, Optimalization, Programming, Software Engineering, Theoretical Computer Science

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Annotation -

Last update: RNDr. Michal Kopecký, Ph.D. (10.05.2017)

The initiative of semantic web can be understood as a project of web content enrichment to improve automated processing. In practice a problem remains: who, why and how it will do. We are treating the problem from SW engineering perspective: models, methodology and process of web semantization. We cover basic formal knowledge necessary for orientation in the field and learn some practical skills. Labs are composed of reporting on current achievements, learning R (GATE) rules for semantization and imitation of a virtual Lean Startup via a social network concentrated on web semantization.

Literature -

Last update: RNDr. Michal Kopecký, Ph.D. (10.05.2017)

Pascal Hitzler, Markus Krötzsch, Sebastian Rudolph. Foundations of Semantic Web Technologies. Chapman & Hall/CRC 2010, http://www.semantic-web-book.org/page/Slides

Eric Ries. Lean Startup, Crown Business 2011

David Harel, Dexter Kozen, Jerzy Tiuryn. Dynamic Logic. Publisher: The MIT Press 2000

G. James, D. Witten, T. Hastie, R. Tibshirani. An Introduction to Statistical Learning with Applications in R. Springer 2013

Syllabus -

Last update: RNDr. Michal Kopecký, Ph.D. (10.05.2017)

Model of web semantization

Basic problems and vision of automation of web content processing,

Lean start-up methodology and semantization

RDF-framework for description of web resources

Data model RDF and RDFS as a model of metadata

Formal semantics of RDF and RDFS - satisfiability

Description logic and the OWL language

Basics of description logic (DeL), knowledge and ontology

Web querying languages

Language SPARQL, SPARQL algebra

Dynamic logic

Propositional dynamic logic (DyL)

Decidability of DyL

Decidability of DyL - completion

Predicate DyL, connections of DyL and web semantization

Model of web semantization

Named entities - recognition and disambiguation

Extraction and annotation of information from web

Model of web semantization (static, dynamic), inductive and deductive parts of the model- Basic models of automated deduction, computational complexity of deduction problems in DeL/OWL

A framework for comparison of models