CE807-7-SP-CO:
Text Analytics
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
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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.
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.
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 |
Description |
Deadline |
Coursework weighting |
Coursework |
Assignment 1 - Text classficiation |
26/02/2018 |
50% |
Coursework |
Assignment 2 - Information extraction |
23/04/2018 |
50% |
Exam format definitions
- Remote, open book: Your exam will take place remotely via an online learning platform. You may refer to any physical or electronic materials during the exam.
- In-person, open book: Your exam will take place on campus under invigilation. You may refer to any physical materials such as paper study notes or a textbook during the exam. Electronic devices may not be used in the exam.
- In-person, open book (restricted): The exam will take place on campus under invigilation. You may refer only to specific physical materials such as a named textbook during the exam. Permitted materials will be specified by your department. Electronic devices may not be used in the exam.
- In-person, closed book: The exam will take place on campus under invigilation. You may not refer to any physical materials or electronic devices during the exam. There may be times when a paper dictionary,
for example, may be permitted in an otherwise closed book exam. Any exceptions will be specified by your department.
Your department will provide further guidance before your exams.
Overall assessment
Reassessment
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.
Yes
No
Yes
Dr Robert Mark Stevenson
University of Sheffield
Senior Lecturer
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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