Programplaner og emneplaner - Student
MBIB4240 Institutions Promoting Information and Culture Course description
- Course name in Norwegian
- Informasjons- og kulturinstitusjoner
- Weight
- 15.0 ECTS
- Year of study
- 2020/2021
- Course history
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Introduction
This course deals with theories, methods and models for constructing, using and evaluating automatic information retrieval systems. This includes input from linguistics, mathematics, statistics and information theory.
- statistic and semantic based methods for document description and retrieval
- automatic classification and categorization
- search behaviour and how to construct systems for real users
- new methods/mediums/arenas for information retrieval, such as image and multimedia retrieval, retrieval of multilingual material etc.
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Required preliminary courses
None
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Learning outcomes
Knowledge
After completion of the course, the student has
- advanced knowledge of the theoretical fundaments for a variety of models for automatic information retrieval, and how the models can be realized with various algorithms
- advanced knowledge of user oriented views on information retrieval, both cognitive and social views, and their consequences for user interface, relevance judgements and interactivity in the retrieval process
- advanced knowledge of linked data and other semantic tools used to structure and make data available, and how to utilize such data
- thoroughly knowledge of practical experiments for evaluating information retrieval systems and models
- advanced knowledge of computational linguistics for analyzing grammar and semantics, and how this can be used in automatic information retrieval system
Skills
After completion of the course, the student can
- participate in, and have practical experience with the development and implementing of user friendly information retrieval systems and modules
- evaluate such systems in order to obtain and use them
General Competene
The student is able to
- give an account of different subdomains that use Information retrieval theories and methods
- independently design, plan, and conduct different types of algorithmic IR related studies, hereunder the choice of appropriate methods and metrics
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Teaching and learning methods
Lectures, tasks and seminars. This includes presentation of a term paper, made individually or in groups, for discussion. Teaching will be in English when there are foreign exchange students present.
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Course requirements
The course requirement is either a report on a laboratory assignment or an essay on one or more of the course subtopics, written either individually or in groups of 2-3 students, to be submitted at the end of the course. The topic of the assignment is chosen in cooperation with a course teacher. The requirement also entails an oral presentation at the end of the course based on a draft. Each student is assigned an opposition of one of the other students' assignments. The course requirement has to be approved to qualify for final grading.
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Assessment
Individual written assignment; the student shall, within the prescribed time limit deliver an individual written 3 days home assignment of 20000 characters +/- 10 per cent. Font and font size: Arial / Calibri 12pkt. Line spacing: 1.5.
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Permitted exam materials and equipment
All examination support materials are permitted. However, sources must be stated in accordance with applicable rules for source references.
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Grading scale
Grading scale A-F.
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Examiners
All exam papers are graded by one internal and one external examiner.
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Target group and admission
The course presupposes knowledge from the bachelor courses BIB3210/BIB3220/BIB3230 or BIB3240/BIB3250/BIB3260.