Students can choose the proper type of knowledge representation for implementing a particular knowledge-based system and are able to implement the knowledge base for a rule-based knowledge representation.
Skills
Knowledge
Students
understand the architecture of knowledge-based systems (K3)
understand and evaluate different types of knowledge representations (K3, K5)
can develop a knowledge base when choosing rule-based knowledge representation (K6)
can design and implement a knowledge-based system with Prolog or Datalog (K6)
understand the foundations of the Sematic Web (K2)
understand and apply case-based reasoning (K2, K3)
Definitions of knowledge
Architecture of knowledge-based systems
Knowledge representation types
Knowledge processing strategies
Foundations of Semantic Web
Case-based reasoning
Prolog
Datalog
Criteria for evaluation
Oral exam at the end of the semester (66%), quality of implementation project (34%)
Methods
Standard lectures with study materials (slides) provided, plus implementing a small project in small groups.
Language
English
Study material
PDF-versions of the slides used in the lecture will be made available via KUSSS.
Additional readings (will not be needed if the lectures are attended on a regular basis):
Rajendra Akerkar, Priti Sajja: Knowledge-Based Systems, Jones & Barlett Pub Inc, 2009
Changing subject?
No
Further information
This lecture is a combined course. It has a lecture part where the foundations are taught and an exercise part where the students have to implement a small knowledge-based system using Prolog or Datalog.
Corresponding lecture
in collaboration with 921INSYASWK13: KV Accessible Software and Web Design (1.5 ECTS) equivalent to INMIPKVKCSY: KV Knowledge-centered Systems (4.5 ECTS)
