Kies de Nederlandse taal
Course module: 2IMW15
Web information retrieval and data mining
Course info
Course module2IMW15
Credits (ECTS)5
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
Responsible lecturer
prof.dr. M. Pechenizkiy
Feedback and reachability
Other course modules lecturer
Contactperson for the course
prof.dr. M. Pechenizkiy
Other course modules lecturer
Academic year2016
1  (05/09/2016 to 13/11/2016)
Starting block
TimeslotB: B - Mo 5-8, Tu 9-10, We 1-4
Course mode
RemarksLast year this subject has been taught: 2016/2017.
Registration openfrom 15/06/2016 up to and including 28/08/2016
Application procedureYou apply via OSIRIS Student
Registration using OSIRISYes
Registration open for students from other department(s)Yes
Waiting listNo
Number of insufficient tests-
Number of groups of preference1
Learning objectives
The objective of this course is to introduce students to the theoretical background and practical aspects of modern Information Retrieval (IR) as well as machine learning/data mining techniques that are used for IR. After taking the course, each student should:
  • know the basic principles and techniques of IR, including also machine learning approaches, for organization and management (e.g. indexing, clustering, classification, matching to user information needs)of various information objects (e.g. documents, Web pages, multimedia);
  • become aware of various application areas of IR, existing IR systems, and challenging research topics in IR;
  • obtain skills for IR design, development and evaluation.

    During the course students will practice different skills studying (research) literature, and working on the individual and group assignments for the course project.
  • Content
    The course 'Information Retrieval' covers the following main topics: classical text retrieval models including Boolean retrieval, vector space retrieval, probabilistic retrieval, and relevance feedback and query expansion mechanisms; information retrieval on the Web, including link mining and web usage mining approaches; and multimedia retrieval. We will also cover data mining foundations for studying the application of learning to rank, classification, clustering and association analysis techniques for better organization of information objects and for user modeling that facilitates personalized and adaptive information retrieval.
    Entrance requirements
    Entrance requirements tests
    Assumed previous knowledge
    2IL05 Data structures
    2DI05 Lineaire algebra
    Previous knowledge can be gained by
    Resources for self study
    Bachelor College or Graduate School
    Graduate School
    URL study guide
    URL study guide
    Informatica, Web Engineering, Tel: 2602, Kamer: MF 7.101, Email:
    Computer science, Web Engineering, Phone: 2602, Room: MF 7.101, Email:
    Required materials
    ISBN: 0521865719. The book is available online (free access) Additional reading material will be provided during the course.
    Title:Introduction to Information Retrieval
    Author:Christopher Manning, Prabhakar Raghavan, Hinrich Schütze
    Publisher:Cambridge University Press, 2008
    Recommended materials
    Instructional modes
    Groupset: 2IMW15


    Test weight100
    Minimum grade6
    Test typeWritten
    Number of opportunities2
    OpportunitiesBlock 1, Block 2
    Test duration in minutes180


    Partial exam (written, open book). There is no resit for the partial exam.

    Group project (report and interactive

    Kies de Nederlandse taal