Knowledge Representation

Code:

MCI0001

Acronym:

RC

Keywords
Classification	Keyword
OFICIAL	Information Science

Instance: 2024/2025 - 1S

Active?	Yes
Web Page:	https://moodle2324.up.pt/course/view.php?id=5390
Responsible unit:	Department of Informatics Engineering
Course/CS Responsible:	Master in Information Science

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
MCI	17	Plano de estudos oficial	1	-	6	42	162

Teaching language

English

Objectives

The "Knowledge Representation" course is based on First-Order Logic and uses it to construct models of the world that can be incorporated into computational systems. Knowledge representation and knowledge-based inference require the identification of ontologies for the selected domains.
Ontology languages embed the semantic web concepts and are powerful tools for any task that requires the analysis of domain knowledge and its mapping into representations that can be automatically processed.
In this unit students are expected to become familiar with the theory and practice of knowledge representation, linking them to their former experience with domain modelling, information description and databases.

Learning outcomes and competences

Upon completion of this course, the student should be able to: 
-Briefly describe the milestones in knowledge representation, in the philosophy and computing domains; 
-Use the concept map technique to capture reality in a selected domain; 
-Use First-Order Logic as a tool for knowledge representation and inference; 
-Relate knowledge representation in logic with data representation in databases; 
-Create an ontology for a domain and explain the choice of the main concepts and relations; 
-Describe the principles of the semantic web and its applications; 
-Choose tools to support the knowledge representation component of a project.

Working method

Presencial

Pre-requirements (prior knowledge) and co-requirements (common knowledge)

Pre-requisites: basic knowledge of conceptual modelling and logic.

Program

Knowledge representation timeline: from Aristotle to Predicate Calculus, to databases, to the semantic web.
Conceptual maps. Concepts. Applications. Tools.
Propositional Logic. Representing facts. Connectives. Inference.
Predicate Logic. Quantification. Inference. Automated reasoning.
The semantic web. Foundations. Data modeling on the web.
Domain ontologies. Selection and representation of an ontology. Ontology languages. OWL. Inference in ontology languages.

Mandatory literature

Barwise, Jon; Language proof and logic. ISBN: 1-889119-08-3
(collective); W3C Data Activity—Building the Web of Data (https://www.w3.org/2013/data/)

Complementary Bibliography

Sowa, John F.; Knowledge representation. ISBN: 0-534-94965-7

Teaching methods and learning activities

Tutorial classes are accompanied by practical sessions, using selected software. Students present their projects in the scheduled sessions. Classes include individual quizzes on previous topics.

Software

Protégé
LPL Software

keywords

Humanities > Information science > Information management > Information processing
Technological sciences > Engineering > Knowledge engineering
Physical sciences > Computer science > Informatics

Evaluation Type

Distributed evaluation without final exam

Assessment Components

Designation	Weight (%)
Teste	30,00
Trabalho escrito	30,00
Trabalho laboratorial	40,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Estudo autónomo	56,00
Frequência das aulas	42,00
Trabalho laboratorial	54,00
Total:	152,00

Eligibility for exams

There is no final exam.
Students are required to have a minimum of 50% on project work (exercises and projects) and a minimum of 50% on individual assignments (quizzes and mini-test).

Calculation formula of final grade

The final grade is computed using the formula
GRADE= round(20% * FOL Project + 25% * FOL Quizzes +  30% * SW Project + 25% * Mini-Test).

Examinations or Special Assignments

None. All students have to complete the projects in the corresponding semester and present them as scheduled.

Special assessment (TE, DA, ...)

All students have to complete the projects and present them in class as scheduled.

Classification improvement

Improving the course grade requires a new enrollment in the course, taking the course projects and tests again.