DD2476 Search Engines and Information Retrieval Systems 9.0 credits

Sökmotorer och informationssökningssystem

A course in computer science focusing on basic theory, models, and methods for information retrieval.

  • Educational level

    Second cycle
  • Academic level (A-D)

  • Subject area

    Computer Science and Engineering
  • Grade scale

    A, B, C, D, E, FX, F

Course offerings

Spring 18 ir18 for single courses students

  • Periods

    Spring 18 P3 (6.0 credits), P4 (3.0 credits)

  • Application code

    20031

  • Start date

    15/01/2018

  • End date

    2018 week: 23

  • Language of instruction

    English

  • Campus

    KTH Campus

  • Number of lectures

    12 (preliminary)

  • Number of exercises

  • Tutoring time

    Daytime

  • Form of study

    Normal

  • Number of places

    No limitation

  • Course responsible

    Johan Boye <jboye@kth.se>

  • Teacher

    Jussi Karlgren <jussi@kth.se>

    Viggo Kann <viggo@kth.se>

  • Target group

    Only open för students within Study Abroad Programme (SAP)

Spring 17 ir17 for programme students

Spring 17 SAP for single courses students

  • Periods

    Spring 17 P3 (6.0 credits), P4 (3.0 credits)

  • Application code

    61059

  • Start date

    2017 week: 3

  • End date

    2017 week: 23

  • Language of instruction

    English

  • Campus

    KTH Campus

  • Number of lectures

    12 (preliminary)

  • Number of exercises

  • Tutoring time

    Daytime

  • Form of study

    Normal

  • Number of places

    No limitation

  • Schedule

    Schedule (new window)

  • Course responsible

    Johan Boye <jboye@kth.se>

  • Teacher

    Jussi Karlgren <jussi@kth.se>

    Viggo Kann <viggo@kth.se>

  • Target group

    Single course students.

Intended learning outcomes

After completing the course you will be able to:

*  explain the concepts of indexing, vocabulary, normalization and dictionary in Information Retrieval,

*  give an account of different text similarity measures, and select a similarity measure suitable for the problem at hand,

*  define a boolean model and a vector space model, and explain the differences between them,

*  implement a method for ranked retrieval of a very large number of documents with hyperlinks between them,

*  evaluate information retrieval algorithms, and give an account of the difficulties of evaluation,

*  give an account of the structure of a Web search engine.

Course main content

Basic and advanced techniques for information systems: information extraction; efficient text indexing; indexing of non-text data; Boolean and vector space retrieval models; evaluation and interface issues; structure of Web search engines.

Eligibility

SF1604 Linear algebra,  SF1901 Probability theory and statistics,  DD1338 Algorithms and Data Structures, or corresponding courses.

Recommended prerequisites

A level in Mathematics corresponding to at least 30 credits, including courses in Linear Algebra and Mathematical Statistics, and a level in Computer Science corresponding to at least 15 credits.

Literature

C. D. Manning, P. Raghavan and H. Schütze: Introduction to Information Retrieval, Cambridge University Press, 2008.

Examination

  • LABA - Laboratory lessons, 6.0, grade scale: A, B, C, D, E, FX, F
  • LABB - Laboratory lessons, 3.0, grade scale: A, B, C, D, E, FX, F

In this course all the regulations of the code of honor at the School of Computer science and Communication apply, see: http://www.kth.se/csc/student/hederskodex/1.17237?l=en_UK.

Offered by

CSC/Speech, Music and Hearing

Contact

Johan Boye, e-post: jboye@kth.se

Examiner

Johan Boye <jboye@kth.se>

Version

Course syllabus valid from: Autumn 2016.
Examination information valid from: Spring 2013.