COURSE UNIT TITLE

: TEXT BASED INFORMATION RETRIEVAL

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
CSE 5061 TEXT BASED INFORMATION RETRIEVAL ELECTIVE 3 0 0 8

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR DERYA BIRANT

Offered to

Industrial Ph.D. Program In Advanced Biomedical Technologies
Industrial Ph.D. Program In Advanced Biomedical Technologies
Computer Engineering (Non-Thesis-Evening) (English)
Computer Engineering Non-Thesis (English)
Biomedical Tehnologies (English)
Computer Engineering (English)
Computer Engineering (English)
COMPUTER ENGINEERING (ENGLISH)

Course Objective

This course introduces the basics of Text Information Retrieval and Text Mining. It focuses both theoretical aspects as well as practical uses of text mining and Information Retrieval .

Learning Outcomes of the Course Unit

1   To understand the difference between data and information retrieval
2   Learn three basic approaches of Information retrieva and text processing
3   Ability to useText mining tools
4   To evaluate a new Information retrieval and text mining approach or ability to chose right

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction to Information Retrieval
2 Boolean retrieval
3 The term vocabulary and postings lists
4 Index construction and compression
5 Scoring, term weighting and the vector space model
6 Computing scores in a complete search system
7 Relevance feedback and query expansion
8 XML retrieval
9 Language models for information retrieval
10 Language models for information retrieval
11 Probabilistic information retrieval
12 Probabilistic information retrieval
13 Student Projects
14 Student Projects

Recomended or Required Reading

Christopher D. Manning, Prabhakar Raghavan, Hinrich Schütze,An Introduction to Information Retrieval, Cambridge University Press, Cambridge, England
Sholom M. Weiss, Nitin Inurkhya, Tong Zhang, "Fundamentals of Predictive Text Mining", Springer, 2010.

Planned Learning Activities and Teaching Methods

Research, Project, Presentation, Report

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 ASG ASSIGNMENT
2 PRS PRESENTATION
3 FCG FINAL COURSE GRADE ASG * 0.50 + PRS * 0.50


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

Research, Project, Presentation, Report

Language of Instruction

English

Course Policies and Rules

Participation is mandatory.

Contact Details for the Lecturer(s)

Prof.Dr. Derya BIRANT
Dokuz Eylul University
Department of Computer Engineering
Tinaztepe Campus, 35390 Izmir, Türkiye
Tel: 232-3017401
E-mail: derya@cs.deu.edu.tr

Office Hours

Monday 9:30 - 12:00

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 3 42
Preparations before/after weekly lectures 14 2 28
Project Preparation 1 65 65
Reading 10 3 30
Preparing presentations 1 20 20
Web Search and Library Research 1 5 5
TOTAL WORKLOAD (hours) 190

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11
LO.15555555
LO.25555555
LO.35555555
LO.45555555