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Knowledge Analysis & Management

Description

COURSE OBJECTIVES

Knowledge extraction and representation are key enablers for data comprehension and decision making. This course will cover techniques for the extraction of knowledge from natural language documents and for the representation of knowledge as ontologies and semantic webs.

 

COURSE DESCRIPTION
Specifically, we will go through text analysis techniques such as part of speech tagging, dependency parsing, text summarization, sentiment analysis, and we will consider knowledge query and representation technologies, such as SPARQL, RDF and OWL.

 

LEARNING METHODS
Students will be involved in practical exercises and will experiment with the presented techniques by applying them to the course projects.

 

EXAMINATION INFORMATION
Optional written midterm exam; oral final exam.

 

RECOMMENDED COURSES

  • Data Design & Modeling
  • Information Modeling & Analysis

 

REFERENCES

  • Lecture slides and lecture notes, available on iCorsi

People

 

Tonella P.

Course director

Humbatova N.

Assistant

Additional information

Semester
Fall
Academic year
2020-2021
ECTS
6
Language
English
Education
Master of Science in Software & Data Engineering, Core course, Lecture, 2nd year