Computer Science and Electronic Engineering (School of)
Postgraduate: Level 7
Monday 15 January 2018
Friday 23 March 2018
25 March 2013
Requisites for this module
MSC G51512 Big Data and Text Analytics
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.
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.
1. Text classification: techniques and applications
2. Sentiment analysis
3. Extracting information from text: entities, relations
4. Summarizing textual information
5. Analyzing social media.
No information available.
No information available.
No additional information available.
Mode of delivery:
2 hours of lectures per week, 2 hours of laboratory time per week.
This module does not appear to have a published bibliography.
Assessment items, weightings and deadlines
|Coursework / exam
||Assignment 1 - Text classficiation
||Assignment 2 - Information extraction
Module supervisor and teaching staff
Dr Alba Garcia Seco De Herrera, email: firstname.lastname@example.org.
School Office, e-mail csee-schooloffice (non-Essex users should add @essex.ac.uk to create full e-mail address), Telephone 01206 872770.
Dr Robert Mark Stevenson
University of Sheffield
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).
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