Text Technologies (Level 10) (VS1) (U02969)

? Credit Points : 10 ? SCQF Level : 10 ? Acronym : INF-4-TTS

This course looks in detail at semi-structured and unstructured data, introduced in Inf 1b. (For students who have taken AI2 and/or CS2, unstructured data corresponds to plain text, while semi-structured data corresponds to text annotated with mark-up, which gives it a light structure. Structured data is corresponds to the data one finds in database).

Text technologies are concerned with people's information needs and the properties of texts, and with exploiting those properties in order to retrieve and synthesise information from large volumes of textual material (such as documents or web pages) in order to meet those needs.

The course will cover:

* Basic concepts and methods for reaslising them, including relevance, text representation, query/question representation, indexing, evaluation, and retrieval models;

* Applications of these concepts and methods in cross-language information retrieval, web searching, collaborative filtering, question answering, information extraction, trust detection, and text mining.

This course is identical to the level 11 version except with respect to assessed weighting, coursework and learning outcomes.

Entry Requirements

? This course is only available to part year visiting students.

? This course is a variant of the following course : U02938

? Pre-requisites : Inf2a OR AI2 OR CS2

? Co-requisites : Knowledge of elementary data structures and probability is needed to understand indexing, retrieval models, and certain text ranking algorithms.

Subject Areas

Home subject area

Informatics, (School of Informatics, Schedule O)

Delivery Information

? Normal year taken : 4th year

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

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

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 computational algorithms used to organise, search and recover information present within large volumes of textual material.
* Evaluate the performance of such algorithms.
* Discuss applications of such techniques in a variety of practical situations.
* Demonstrate an understanding of how to successfully recover information from large volumes of texts.