CE306-6-SP-CO:
Information Retrieval
2024/25
Computer Science and Electronic Engineering (School of)
Colchester Campus
Spring
Undergraduate: Level 6
Current
Monday 13 January 2025
Friday 21 March 2025
15
02 May 2024
Requisites for this module
(none)
(none)
(none)
(none)
(none)
BSC I1G3 Data Science and Analytics,
BSC I1GB Data Science and Analytics (Including Placement Year),
BSC I1GC Data Science and Analytics (Including Year Abroad),
BSC I1GF Data Science and Analytics (Including Foundation Year),
BSC LG01 Economics with Data Science,
BSC LG02 Economics with Data Science (Including Year Abroad),
BSC LG03 Economics with Data Science (Including Placement Year),
BSC LG04 Economics with Data Science (Including Foundation Year),
BSC L310 Sociology with Data Science,
BSC L311 Sociology with Data Science (including Year Abroad),
BSC L312 Sociology with Data Science (including Placement Year),
BSC L313 Sociology with Data Science (Including foundation Year),
BSC LL20 Politics with Data Science
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 aim of this module is:
- To teach students how to design, build and evaluate an information retrieval system, and to provide the essential foundations of information retrieval and 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.
- Understand standard IR models and their merits and limitations.
- Demonstrate an understanding of commonly used evaluation approaches in IR.
- Understand advanced concepts of search applications.
Outline Syllabus:
- Term Frequency
- Inverted Document Frequency
- Inverted Indexing
- Processing Pipelines
- Evaluation
- Neural Network Approaches
- Research Topics
This module will be delivered via:
- Lectures,
- Laboratories and
- Classes
-
Croft, W.B., Metzler, D. and Strohman, T. (2015)
Search engines: information retrieval in practice. International ed. Boston: Pearson Education. Available at:
http://ciir.cs.umass.edu/downloads/SEIRiP.pdf.
-
Garg, M., Kumar, S. and Khader Jilani Saudagar, A. (eds) (2023)
Natural Language Processing and Information Retrieval. London: Taylor & Francis Ebooks. Available at:
https://app.kortext.com/Shibboleth.sso/Login?entityID=https://idp0.essex.ac.uk/shibboleth&target=https://app.kortext.com/borrow/2474598.
-
Gao, J.
et al. (2023)
Neural Approaches to Conversational Information Retrieval. Cham: Springer International Publishing. Available at:
https://doi.org/10.48550/arXiv.2201.05176.
-
Sakai, T., Oard, D.W. and Kando, N. (eds) (2021)
Evaluating Information Retrieval and Access Tasks. Singapore: Springer Singapore. Available at:
https://doi.org/10.1007/978-981-15-5554-1.
-
Mitra, B. and Craswell, N. (2018)
Introduction to Neural Information Retrieval. Hanover: now publishers Inc. Available at:
https://doi.org/10.1561/1500000061.
-
Russell-Rose, T. and Tate, T. (2013)
Designing the search experience: the information architecture of discovery. 1st edition. Amsterdam: Elsevier, Morgan Kaufmann. Available at:
https://learning.oreilly.com/library/view/designing-the-search/9780123969811/?sso_link=yes&sso_link_from=university-of-essex.
-
Manning, C.D., Raghavan, P. and Schu¨tze, H. (2008)
Introduction to information retrieval. Cambridge: Cambridge University Press. Available at:
https://search-ebscohost-com.uniessexlib.idm.oclc.org/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=304660.
-
Baeza-Yates, R. and Ribeiro-Neto, B. (2011) Modern information retrieval: the concepts and technology behind search. Second edition. Harlow: Pearson Addison-Wesley.
-
Salton, G. (1989) Automatic Text Processing: The Transformation, Analysis, and Retrieval of Information by Computer. Addison-Wesley Publishing Company.
-
Lalmas, M., Van Rijsbergen, C.J. and Crestani, F. (eds) (1998)
Information retrieval, uncertainty and logics: advanced models for the representation and retrieval of information. 1st ed. 1998. Boston, Massachusetts: Kluwer Academic Publishers. Available at:
https://ebookcentral.proquest.com/lib/universityofessex-ebooks/detail.action?docID=6497844.
The above list is indicative of the essential reading for the course.
The library makes provision for all reading list items, with digital provision where possible, and these resources are shared between students.
Further reading can be obtained from this module's
reading list.
Assessment items, weightings and deadlines
| Coursework / exam |
Description |
Deadline |
Coursework weighting |
| Coursework |
Progress Test (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 Early Exams
|
| 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
No
No
Yes
Available via Moodle
Of 50 hours, 22 (44%) hours available to students:
24 hours not recorded due to service coverage or fault;
4 hours not recorded due to opt-out by lecturer(s), module, or event type.
Disclaimer: The University makes every effort to ensure that this information on its Module Directory is accurate and up-to-date. Exceptionally it can
be necessary to make changes, for example to programmes, modules, facilities or fees. Examples of such reasons might include a change of law or regulatory requirements,
industrial action, lack of demand, departure of key personnel, change in government policy, or withdrawal/reduction of funding. Changes to modules may for example consist
of variations to the content and method of delivery or assessment of modules and other services, to discontinue modules and other services and to merge or combine modules.
The University will endeavour to keep such changes to a minimum, and will also keep students informed appropriately by updating our programme specifications and module directory.
The full Procedures, Rules and Regulations of the University governing how it operates are set out in the Charter, Statutes and Ordinances and in the University Regulations, Policy and Procedures.