CE706-7-SP-CO:
Information Retrieval
2024/25
Computer Science and Electronic Engineering (School of)
Colchester Campus
Spring
Postgraduate: Level 7
Current
Monday 13 January 2025
Friday 21 March 2025
15
27 August 2024
Requisites for this module
(none)
(none)
(none)
CE306
(none)
MSC G51512 Big Data and Text Analytics,
MSC G412JS Applications of Artificial Intelligence,
MSC G456N3 Computing
Students are not permitted to undertake this module if they have done the equivalent module of CE306 at UG level on a CSEE undergraduate course. This is because it cannot count towards your course credits. Please contact the CSEE School Office for specific advice on your module choices.
Search engines have become the first entry point into a world of knowledge and they form an essential part of many modern computer applications. While many of the underlying principles have been developed over decades, the landscape in search engine technology has changed dramatically in recent years to deal with data sources which are magnitudes larger than ever before (the rise of ‘big data’).
As a result, new paradigms for storing, indexing and accessing information have emerged. This module will describe the essential foundations of information retrieval and equip the students with solid, applicable knowledge of state-of-the-art search technology.
The aims of the module are:
- To teach students how to design, build and evaluate an information retrieval system, and to provide the essential foundations of information retrieval
- To describe key research issues and possible future developments
By the end of this module, students will be expected to be able to:
- Design and implement a standard information retrieval system.
- Critically evaluate standard IR models and their merits and limitations.
- Demonstrate a comprehensive understanding of commonly used evaluation approaches in IR.
- Apply advanced concepts of search applications.
Indicative Syllabus:
- Term Frequency
- Inverted Document Frequency
- Inverted Indexing
- Processing Pipelines
- Evaluation
- Neural Network Approaches
- Research Topics
This module will be delivered via:
- Lectures, lab sessions and classes
This module does not appear to have a published bibliography for this year.
Assessment items, weightings and deadlines
| Coursework / exam |
Description |
Deadline |
Coursework weighting |
| Coursework |
Progress Test, week 23 (invigilated in CSEE labs, closed book, on Moodle, MCQ) |
|
25% |
| Coursework |
Coding Exercise |
28/02/2025 |
75% |
| Exam |
Main exam: In-Person, Open Book (Restricted), 120 minutes during Summer (Main Period)
|
| Exam |
Reassessment Main exam: In-Person, Open Book (Restricted), 120 minutes during September (Reassessment Period)
|
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 Richard Sutcliffe, email: rsutcl@essex.ac.uk.
Dr Richard Sutcliffe
School Office, email: csee-schooloffice (non-Essex users should add @essex.ac.uk to create full e-mail address), Telephone 01206 872770
Yes
No
Yes
Dr Colin Johnson
University of Nottingham
Dr MARJORY CRISTIANY Da COSTA ABREU
Sheffield Hallam University
Senior Lecturer
Available via Moodle
Of 1089 hours, 0 (0%) hours available to students:
1089 hours not recorded due to service coverage or fault;
0 hours not recorded due to opt-out by lecturer(s).
* Please note: due to differing publication schedules, items marked with an asterisk (*) base their information upon the previous academic year.
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