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Syllabus 2019-20 - 13312034 - Intelligent Information Systems (Sistemas inteligentes de información)

Caption
  • Level 1: Tutorial support sessions, materials and exams in this language
  • Level 2: Tutorial support sessions, materials, exams and seminars in this language
  • Level 3: Tutorial support sessions, materials, exams, seminars and regular lectures in this language
DEGREE: Grado en Ingeniería informática
FACULTY: SCHOOL OF ENGINEERING OF JAÉN

ACADEMIC YEAR: 2019-20
SYLLABUS
1. COURSE BASIC INFORMATION
NAME: Intelligent Information Systems
CODE: 13312034 ACADEMIC YEAR: 2019-20
LANGUAGE: English LEVEL: 2
ECTS CREDITS: 6.0 YEAR: 3 SEMESTER: SC
 
2. LECTURER BASIC INFORMATION
NAME: GACTO COLORADO, Mª JOSÉ
DEPARTMENT: U118 - INFORMÁTICA
FIELD OF STUDY: 075 - CIENCIA DE LA COMPUTACIÓN E INT. ARTIFICIAL
OFFICE NO.: A3 - 243 E-MAIL: mgacto@ujaen.es P: 953212261
WEBSITE: http://wwwdi.ujaen.es/?q=es/mgacto
LANGUAGE: - LEVEL: 2
 
3. CONTENT DESCRIPTION

THEORY

Module 1: Introduction to knowledge representation.

    Topic 1: Acquisition and representation of knowledge.
    Topic 2: Knowledge engineering: ontologies.

Module 2: Basic models of knowledge representation.

    Topic 3: Logical models. First order logic
    Topic 4: Inference in first order logic.
    Topic 5: Rule-based systems.
    Topic 6: Structured models. Semantic networks.

Module 3: Advanced models of knowledge representation.

    Topic 7: Representation of uncertainty. Bayesian networks.
    Topic 8: Fuzzy Rule-based systems.
    Topic 9: Introduction to Big Data.

PRACTICES

Development, implementation and analysis of a classification and / or regression algorithm related to the subject matter studied in the subject.

4. COURSE DESCRIPTION AND TEACHING METHODOLOGY

The subject is divided into two related parts, theory and practices.

The theory will be taught mainly through lectures, including sessions of activities, resolution of doubts and debate with which the participation of the student in the subject will be evaluated.

The practical part will be done in the computer lab.

The seminars will be taught in computer labs. In them several software of different nature will be studied:
    - Protégé, open source ontology publisher abr framework for building intelligent system.
    - KEEL (Knowledge Extraction based on Evolutionary Learning)
    - Software for fuzzy: JFML (Java Fuzzy Markup Language), Fuzzy Logic Toolbox (MATLAB - MathWorks), etc.

Students with special educational needs should contact the Student Attention Service (Servicio de Atención y Ayudas al Estudiante) in order to receive the appropriate academic support

5. ASSESSMENT METHODOLOGY

To pass the subject it will be necessary to approve both the theoretical part and the practical part.

As specified in art. 13 of the Regulation of Academic Regime and Evaluation of the students of the University of Jaén, the evaluation of the subject will be global. Similarly, in accordance with art. 18 of the aforementioned Regulation, a call will be considered exhausted when the evaluation tests in which the student had participated together represent more than 30% of the final grade of the subject.



The theoretical part will be evaluated with an objective test of theoretical concepts and realization of practical exercises related to the subject. The part of practices will be evaluated by means of the delivery of practical works carried out with a computer and with a justifying memory associated to them. The evaluation of the practices will be continuous and incremental, in such a way that both the defense of the practical project carried out in the delivery and the evolution of the student during the practical sessions will be evaluated.

Competencies for the Evaluation System:

    S1 (attendance and participation): CT6, CS12, CS16

    S2 (theoretical knowledge): CT6, CS12, CS16

    S4 (Computer practices): CS12, CS16

   
Results by Evaluation System:

    S1 (attendance and participation): 2,3,6,8

    S2 (theoretical knowledge): 2,3,6,8

    S4 (Computer practices): 2,3,6

6. BOOKLIST
MAIN BOOKLIST:
  • Introduction to machine learning. Edition: 2nd ed.. Author: Alpaydin, Ethem.. Publisher: Cambridge, Mass. : MIT Press, 2010  (Library)
  • Fuzzy set theory and its applications . Edition: -. Author: Zimmermann, H.-J.. Publisher: Boston : Kluwer Academic Publishers, cop. 2001  (Library)
  • Artificial intelligence: a modern approach. Edition: 3rd th. Author: Russell, Stuart J.. Publisher: Boston [etc.] : Pearson Education, 2010  (Library)
ADDITIONAL BOOKLIST:
  • Hadoop [Recurso electrónico] : the definitive guide. Edition: 3rd ed. Author: White, Tom (Tom E.). Publisher: Sebastopol, CA : O'Reilly, 2012  (Library)
  • Pattern Recognition and Machine Learning [Recurso electrónico]. Edition: -. Author: Bishop, Christopher M.. Publisher: New York, NY : Springer Science+Business Media, LLC, 2006.  (Library)
  • Bayesian artificial intelligence. Edition: 2nd ed.. Author: Korb, Kevin B.. Publisher: Boca Raton, FL : CRC Press, c2011  (Library)