Text Technologies (Level 11) (P00955)

? Credit Points : 10 ? SCQF Level : 11 ? Acronym : INF-P-TTS

The course deals with retrieval technologies behind search engines, such as Google. The course will aim to strike a balance between theoretical and system-related aspects of the field. The course will cover:

Theoretical aspects, including properties of text, queries, relevance, major retrieval models and evaluation;

System-related aspects, including crawlers, text processing, index construction and retrieval algorithms;

Applications, including cross-language and multi-media search.

The same material will be covered in the level 10 and level 11 versions of the course. Level 11 students should expect more challenging assignments and an increased programming load.

Entry Requirements

? Pre-requisites : For Informatics PG students and final year MInf students only, or by special permission of the School. Students must be able to program. An appreciation of topics in computer science, probability and natural language processing will enhance one's understanding of the material to be covered in the course.

? Prohibited combinations : Text Technologies (Level 10)

Subject Areas

Home subject area

Artificial Intelligence, (School of Informatics, Schedule O)

Other subject areas

Computational Linguistics, (School of Informatics, Schedule O)

Cognitive Science, (School of Informatics, Schedule O)

Delivery Information

? Normal year taken : Postgraduate

? Delivery Period : Semester 1 (Blocks 1-2)

? Contact Teaching Time : 2 hour(s) per week for 10 weeks

First Class Information

Date	Start	End	Room	Area	Additional Information
25/09/2008	12:10	13:00	Room G.02, William Robertson Building	Central

All of the following classes

Type	Day	Start	End	Area
Lecture	Monday	12:10	13:00	Central
Lecture	Thursday	12:10	13:00	Central

Summary of Intended Learning Outcomes

It is anticipated that students who successfully complete the course will be able to:
-Describe the main algorithms for processing, storing and retrieving text.
-Show familiarity with theoretical aspects of IR, including the major retrieval models.
-Discuss the range of issues involved in building a real search engine.
-Evaluate the effectiveness of a retrieval algorithm.