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Course module: 2IMW00
2IMW00
Seminar web engineering
Course info
Course module2IMW00
Credits (ECTS)5
Category-
Course typeGraduate School
Language of instructionEnglish
Offered byEindhoven University of Technology; Mathematics and Computer Science; Computer Science;
Is part of
Business Information Systems
Computer Science and Engineering
Contact personprof.dr. M. Pechenizkiy
Telephone-
E-mailm.pechenizkiy@tue.nl
Lecturer(s)
Co-lecturer
prof.dr. P.M.E. De Bra
Other course modules lecturer
Responsible lecturer
dr. G.H.L. Fletcher
Other course modules lecturer
Contactperson for the course
prof.dr. M. Pechenizkiy
Other course modules lecturer
Co-lecturer
dr. N. Yakovets
Other course modules lecturer
Academic year2016
Period
2  (14/11/2016 to 05/02/2017)
Starting block
2
TimeslotD2: D2 - We 7-8, Fr 3-4
Course mode
Fulltime
RemarksLast year this subject has been taught: 2016/2017.
Registration openfrom 15/06/2016 up to and including 23/10/2016
Application procedureYou apply via OSIRIS Student
Explanation-
Registration using OSIRISYes
Registration open for students from other department(s)Yes
Pre-registrationNo
Waiting listNo
Number of insufficient tests-
Number of groups of preference1
Learning objectives
This seminar focuses on studying selected topics and the current state of the art in the areas of data mining, information retrieval, adaptive systems, and recommender systems as well as their various cross-roads. Topics to be chosen are not fixed and may depend (each year) on the preference of DH group and students enrolled in the seminar.
Please notice that this seminar series first of all is aimed to help master level students in preparation for their graduation projects. Therefore, a reasonable degree of freedom will be given in the selection of topics and assignments.
The students taking this seminar are expected:
  • to provide an overview (with a focus on research questions) of the important research papers in these areas,
  • to study common underlying techniques and research methods,
  • to find/identify potential research projects, and
  • to conduct experiments (or develop a framework; depends on a selected topic/assignment) and report the findings
  • to present and defend the obtained results.
  • Content
    A list of recommended titles and reading material will be made available shortly after the start of the course and the list of participants is known. We kindly ask you to register to this course at your earliest convenience, following the instructions at the course web page.
    The topics may include (but are not limited to) advanced and novel data mining techniques, handling streaming data, different aspects of personalization and adaptation in IS, user modeling, context-awareness, privacy-preservation and discrimination awareness, domain knowledge integration, developing generic adaptation and data mining frameworks and approaches, and developing specialized applications.
    Entrance requirements
    Entrance requirements tests
    -
    Assumed previous knowledge
    -
    Previous knowledge can be gained by
    -
    Resources for self study
    -
    Bachelor College or Graduate School
    Graduate School
    URL study guide
    http://wwwis.win.tue.nl/2ID95/
    URL study guide
    http://wwwis.win.tue.nl/2ID95/
    Required materials
    -
    Recommended materials
    Course materials will be provided along the duration of the seminar.
    Instructional modes
    College / course

    General
    -

    Remark
    -
    Tests
    Assignment(s)
    Test weight100
    Minimum grade6
    Test typeAssignment(s)
    Number of opportunities1
    OpportunitiesBlock 2
    Test duration in minutes-

    Assessment
    -

    Remark
    100% individual project work

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