Research Topics in Cognitive Computing
Level of Study
Objectives and Content
The course will provide the theoretical and technical background for implementing information systems which can behave in human like ways. This involves natural language processing, visual recognition, and a deep representation of the meaning of information. We will also consider theories of human cognition to learn from the differences between human and machine systems of information processing.
Students will also explore the concept of symbiotic systems, which will give them the skills to implement intelligent software applications that optimally compliments human users.
The course will also provide the academic background for supervised research on information systems that are based on cognitive, symbiotic models. Examples of research and research methods in the area will also be presented and discussed.
Upon completion of the course the candidate should be able to
- demonstrate an understanding for central concepts in information systems interoperability.
- describe and discuss human centric notions of semantics
- explain the way Natural Language Processing (NLP) is used in semantic models
- explain what cognitive and symbiotic systems mean in information systems
Required Previous Knowledge
Bachelor's degree in information science or equivalent.
Access to the Course
Master in Information Science. Other master students may apply for admission.
Teaching and learning methods
Lectures, exercises, student presentations and discussions (around 40 hours, of which around 20-24 hours are lectures)
Compulsory Assignments and Attendance
Participation at 80% of course seminars is mandatory.
Compulsory requirements are only valid the semester they are approved.
Forms of Assessment
- Individual, theoretical essay with thoughtful research and discussion of an assigned topic (60%).
- Practical assignment in groups (40%).
Both assignments must be done in the teaching semester.
The grading system has a descending scale from A to E for passes and F for fail.
Assessment in teaching semester.
All courses are evaluated according to UiB's system for quality assurance of education.
Studierettleiar kan kontaktast her: email@example.com / 55 58 90 00