EPN-V2

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
  • 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.
  • Required preliminary courses

    None

  • 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
  • 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.

  • 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.

  • 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.

  • Permitted exam materials and equipment

    All examination support materials are permitted. However, sources must be stated in accordance with applicable rules for source references.

  • Grading scale

    Grading scale A-F.

  • Examiners

    All exam papers are graded by one internal and one external examiner.

  • Target group and admission

    The course presupposes knowledge from the bachelor courses BIB3210/BIB3220/BIB3230 or BIB3240/BIB3250/BIB3260.