|Title: ||Ανάκτηση Πληροφορίας|
|Lesson Code: ||321-10202|
|Theory Hours: ||3|
|Lab Hours: |
|Faculty: ||Vasilopoulos Nikolaos|
Introduction to information retrieval systems. Information retrieval/filtering and browsing. Modeling: Set theoretic models, Algebraic models, Probabilistic models. Text processing and compression. Zipf's law and Heaps' law. Introduction to markup languages. Indexing methods: inverted files, suffix trees and arrays, signature files. Online search methods. Evaluation of information retrieval systems. User feedback and query expansion. Web search: search engines, web crawling techniques, link-based methods.
Understanding of the distinction between data retrieval and information retrieval. Familiarity with the architecture of an information retrieval system. Understanding of the properties of the Boolean, Vector-space, and Probabilistic models for information retrieval. Familiarity with the basic principles of text processing and basic properties of text corpora. Understanding of the most popular indexing methods used in information retrieval systems. Ability to evaluate information retrieval systems. Familiarity with user feedback and query expansion methods. Understanding of the properties of web information retrieval. Familiarity with web crawling techniques.
1. Christopher Manning, Prabhakar Raghavan, Hinrich Schutze, Introduction to Information Retrieval, Stanford NLP Group, 2009.
1. Baeza-Yates and Ribeiro-Neto, “Modern Information Retrieval”, Addision Wesley, 1999.
2. Witten, Moffat, and Bell, “Managing Gigabytes: Compressing and Indexing Documents and Images”, Morgan Kaufmann Publishing, 1999.
3. C. J. van Rijsbergen, “Information Retrieval”, 2nd edition, 1979.
|Learning Activities and Teaching Methods |
Final written exam, personal project.
|Assessment/Grading Methods |
||125 hours (5 ECTS)
|Language of Instruction|
|Greek, English (for Erasmus students)|
|Μode of delivery |