Information Retrieval (IR) systems give access to large amounts of online information stored as text, images, speech or video, or composite forms e.g. Web documents. IR systems should only retrieve those documents that are relevant to a user's interest but have to deal with the uncertainty of describing what a document is about and what a user is actually interested in. This course aims at introducing the area of Information Retrieval and at examining the theoretical and practical issues involved in designing, implementing and evaluating Information Retrieval systems.
The purpose of the course is to introduce the area of information retrieval systems and to examine the theoretical and practical issues related to the design, implementation, and evaluation of such systems.
Content Organization
Introduction
What is Information Retrieval / Basic concepts
Historical background
Information Retrieval Models
Boolean
Vector
Probabilistic
Alternative models
Evaluation of Information Retrieval Systems' Effectiveness
Precision and Recall
Alternative measures
Reference collections and system evaluation
Query Languages for Information Retrieval
Keywords
Logical queries
Contextual queries
Natural language queries
Structured queries
Advanced Query Operations
Relevance feedback
Query expansion
Automatic local/global analysis
Indexing, Preprocessing, and Organization of Text Files
Spatial access structures and searching in multidimensional spaces
Parallel and Distributed Information Retrieval
MIMD and SIMD architectures
Collection partitioning
Source selection
Query processing
Meta-Ranking Techniques
Web Search
Historical background
Webpage indexing
Web crawling
Link analysis techniques
User interfaces and visualization
Information Retrieval (IR) systems give access to large amounts of online information stored as text, images, speech or video, or composite forms e.g. Web documents. IR systems should only retrieve those documents that are relevant to a user's interest but have to deal with the uncertainty of describing what a document is about and what a user is actually interested in. This course aims at introducing the area of Information Retrieval and at examining the theoretical and practical issues involved in designing, implementing and evaluating Information Retrieval systems.
Learning Outcomes
Students who successfully complete the course will have acquired: Knowledge: Students will have learned the theoretical foundation of established retrieval models (Boolean, Vector-space, Probabilistic, Logical models), the methods and metrics for evaluating the effectiveness of information retrieval systems, and indexes and techniques for implementing such systems. Understanding: Students will have understood the difficulty of representing and retrieving documents, images, speech, etc., and will have comprehended methods and techniques to address this problem. Application: Students will be able to apply their knowledge to design and implement information retrieval systems and evaluate the quality of these systems. Analysis: Students will be able to determine the logic for solving a retrieval problem from its description by utilizing the concepts, methods, and techniques in the field of information retrieval. Synthesis: Students will be able to combine the knowledge and skills they have developed, along with existing software subsystems, to design and implement an information retrieval system and evaluate its performance. Evaluation: Students will be able to test and evaluate an information retrieval system based on various criteria.
Student Performance Evaluation
Specific details on grading can be found on the course’ s website
The courses of the Computer Science Department are designated with the letters "CS" followed by three decimal digits. The first digit denotes the year of study during which students are expected to enroll in the course.
First Digit
Advised Year of Enrollment
1,2,3,4
First, Second, Third and Fourth year
5,6
Graduate courses
7,8,9
Specialized topics
Code
Computer Science Area
A1
Computer architecture and microelectronics
A2
Computer systems, parallel and high performance computing
A3
Computer security and distributed systems
A4
Computer networks, mobile computing, and telecommunications
B1
Algorithms and systems analysis
B2
Databases, information and knowledge management
B3
Software engineering and programming languages
B4
Artificial Intelligence and machine learning
C1
Signal processing and analysis
C2
Computer vision and robotics
C3
Computer graphics and human-computer interaction
C4
Βioinformatics, medical informatics, and computational neuroscience
The following pages contain tables (one for each course category) summarizing courses offered by the undergraduate studies program of the Computer Science Department at the University of Crete. Courses with code-names beginning with "MATH" or "PHYS" are taught by the Mathematics Department and Physics Department respectively at the University of Crete.
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