Information Retrieval

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Course Level: 
Forth Year
Course Code: 
Course Outline: 

Course title and number

Information Retrieval systems

Instructor(s) name(s)

Dr. Fady Draidi

Intended learning


On completion of this course, students should be able to

1.      Provides an introduction to information retrieval systems and different approaches of information retrieval

2.      Understand the evaluation techniques of information retrieval systems such as relevance ranking, recall, precision, average precision

3.      Explain the information retrieval storage methods such as  Inverted Index and Signature Files

4.      Explain retrieval strategies, such as Boolean model, Vector Space model, Probabilistic model, Inference Networks, and Neural Networks.

5.      Explain retrieval utilities such as Stemming, Relevance Feedback, N-gram, Clustering, and Thesauri, and Parsing and Token recognition.

6.      Design and implement a search engine prototype using the storage methods, retrieval models and utilities.

7.      Design and implement information retrieval systems such as web filtering, recommendation systems, cross-language IR, multimedia IR, and machine learning for information retrieval

8.      Apply theories to effectively solve information retrieval problems in real world situations



Textbook and 

Introduction to Information Retrieval, Cambridge University Press. 2008. Christopher D. Manning, Prabhakar Raghavan and Hinrich Schütze


·         Modern Information Retrieval. Ricardo Baeza-Yates & Berthier Ribeiro-Neto ,

·         van Rijsbergen, C. J.  Information Retrieval. (Second Edition) Butterworth's (Boston, MA), 1979. (Full text of the book is available on the web).

·         Frakes, W. B. & Baeza-Yates, R. Information Retrieval: Data Structures & Algorithms. Prentice Hall (Englewood Cliffs, NJ) (ISBN: 0-13-463837-9). 1992.

·         Web Sites:




Assessment Criteria


Percent (%)

First hour Exam


Second Hour Exam


Assignment Project




Final Exam



Course Contents

Introduction -What is Information Retrieval

·          Introduction

·         Users and user's information needs

·         Data, information and documents

·         Past, present and future of IR


Models of Information Retrieval
Inverted indexing

·         Boolean logic

·         Vector model

·         Alternative models

·         Models for browsing

Retrieval Evaluation

·         Relevance

·         Recall & Precision

·         Similarity measure

·         Evaluation of IR systems

·         IR retrieval experiments

Query Languages and Query Operations

·         Basic queries

·         Structural queries

·         Query expansion

Text Retrieval and Languages

 Word extraction

·         Stop words

·         stemming

·         Word frequency counts

·         Zipf's Law

Indexing and Searching

·         Inverted indexing

·         Subject indexing and metadata

·         Citation indexing

·         Term associations & co-occurrences

Effectiveness Improvement Techniques

·         Overview of some practical IR systems

·         Statistical ranking

·         User profiles

IR Research and Future of IR Systems