TU Delft
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2016/2017 Electrical Engineering, Mathematics and Computer Science Master Computer Science
Information Retrieval
Responsible Instructor
Name E-mail
A. Bozzon    A.Bozzon@tudelft.nl
Contact Hours / Week x/x/x/x
Education Period
Start Education
Exam Period
Course Language
Expected prior knowledge
Knowledge of basic algebra. Proficiency in at least one programming language. Knowledge of Web information systems and software engineering can be helpful.
Course Contents
Retrieving relevant information is one of the central activities in modern knowledge-driven societies. As the amount and variety of data increase at an unprecedented rate, access to relevant, possibly unstructured information is becoming more and more challenging. The World Wide Web is now the primary source of information for leisure and work activities. The real value of the Web can only be unlocked if the huge amount of available data can be found, analysed, and exploited so that each user can quickly find information that is both relevant and comprehensive for their needs.

Information Retrieval (IR) is the discipline that deals with the representation, storage, organisation of, and access to information items, and it is concerned with providing efficient access to large amounts of unstructured contents, such as text, images, videos etc. The objective of the IN4325 - Information Retrieval course is to introduce the scientific underpinnings of the field of Information Retrieval. The course aims at providing students basic information retrieval concepts and more advanced techniques for efficient data processing, storage, and querying. Students are also provided with a rich and comprehensive catalogue of information search tools that can be exploited in the design and implementation of Web and Enterprise search engines.

Covered topics include:

= Basic IR Models (boolean, vector-based, probabilistic); Basic Indexing Techniques; Term Weighting and Scoring;
= Web Search;
= Relevance Feedback and Query Expansion;
= Semantic Search
= Information Seeking Paradigms
= Evaluation of information retrieval systems;
= Crowdsourcing, Human Computation, and Games With a Purpose
Study Goals
At the completion of this course, students will be able to:

= Describe the different information retrieval models, and to compare their weaknesses and strengths. [Learning Objective 1]

= Compare the weaknesses and strengths of different indexing techniques, describing their most suited applications trough meaningful examples. [Learning Objective 2]

= Compare the weaknesses and strengths of different querying techniques, describing their most suited applications trough meaningful examples. [Learning Objective 3]

= Analyse the performance of an Information Retrieval system by applying the proper evaluation measures. [Learning Objective 4]

= Design and develop (Web) Information Retrieval systems, possibly using advanced social and se- mantic search functionalities. Support and defend the relevance and correctness of his/her choices with regards to the adopted information retrieval model, indexing technique, and querying tech- nique. [Learning Objective 5]

= Describe and compare several crowdsourcing techniques. [Learning Objective 6]

= Illustrate Information Retrieval application scenario for crowdsourcing. [Learning Objective 7]

= Design and develop crowdsourcing applications, and to evaluate the obtained results. [Learning Objective 8]

= Illustrate suitable application scenario for advanced Information Retrieval topics such as Semantic Search, Information Seeking Paradigms and User Interfaces for Information Retrieval, Search Results Diversification, and Expert Finding. [Learning Objective 9]
Education Method
Lectures; individual weekly assignments; group assignment with plenary presentation and discussion; final individual survey.

Expected workload is 42 hours for attending lectures and meetings with the lecturers, 24 hours of reading study material and preparing lectures, 45 hours for individual and group assignment, 24 hours for preparing final survey, and 5 hours for exam and plenary presentations (total 140 hours)
Literature and Study Materials
Scientific papers, course slides and blackboard notes.
*Introduction to Information Retrieval*
Author(s): Christopher D. Manning, Prabhakar Raghavan and Hinrich Schtze.
Cambridge University Press. 2008. ISBN-13: ISBN-13: 978-0521865715

*Web Information Retrieval*.
Author(s): Stefano Ceri, Alessandro Bozzon, Marco Brambilla, Piero Fraternali, Emanuele Della Valle, Silvia Quarteroni.
Springer, 2013. ISBN-13: 978-3642393136
Weekly Individual assignment, weighting 10% of the final grade
Group assignment, weighting 60% of the final grade
Final Individual Assignment (Survey), weighting 30% of the final grade

The group assignment is performed collectively, but graded individually. Assignments have no resit opportunities.