CE807-7-SP-CO:
Text Analytics

The details
2017/18
Computer Science and Electronic Engineering (School of)
Colchester Campus
Spring
Postgraduate: Level 7
Current
Monday 15 January 2018
Friday 23 March 2018
15
25 March 2013

 

Requisites for this module
(none)
(none)
(none)
(none)

 

(none)

Key module for

MSC G51512 Big Data and Text Analytics

Module description

The aim of this module is to provide students with an understanding of text analytics and its applications. Students will be introduced to state of the art methods for extracting structured information (e.g. opinions about products) from unstructured textual data, in particular in social media; and to techniques for summarizing and analyzing this information.

Learning Outcomes:

After completing this module, students will be expected to be able to:

1. Use text classification techniques for a variety of applications
2. Develop systems for identifying the entities mentioned in text, the relations between them, and the opinions expressed about these entities
3. Analyze data extracted from social media such as blogs and tweets
4. Develop systems for summarizing textual information.

Outline Syllabus:

1. Text classification: techniques and applications

2. Sentiment analysis

3. Extracting information from text: entities, relations

4. Summarizing textual information

5. Analyzing social media.

Module aims

No information available.

Module learning outcomes

No information available.

Module information

No additional information available.

Learning and teaching methods

Mode of delivery: 2 hours of lectures per week, 2 hours of laboratory time per week.

Bibliography

This module does not appear to have a published bibliography.

Assessment items, weightings and deadlines

Coursework / exam Description Deadline Weighting
Coursework   Assignment 1 - Text classficiation  26/02/2018  50% 
Coursework   Assignment 2 - Information extraction  23/04/2018  50% 

Overall assessment

Coursework Exam
100% 0%

Reassessment

Coursework Exam
0% 0%
Module supervisor and teaching staff
Dr Alba Garcia Seco De Herrera, email: alba.garcia@essex.ac.uk.
School Office, e-mail csee-schooloffice (non-Essex users should add @essex.ac.uk to create full e-mail address), Telephone 01206 872770.

 

Availability
Yes
No
Yes

External examiner

Dr Robert Mark Stevenson
University of Sheffield
Senior Lecturer
Resources
Available via Moodle
Of 38 hours, 20 (52.6%) hours available to students:
18 hours not recorded due to service coverage or fault;
0 hours not recorded due to opt-out by lecturer(s).

 

Further information

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