CE306-6-FY-KS:
Information Retrieval
2024/25
Computer Science and Electronic Engineering (School of)
Kaplan Singapore
Full Year
Undergraduate: Level 6
Current
Thursday 03 October 2024
Friday 27 June 2025
15
08 November 2023
Requisites for this module
(none)
(none)
(none)
(none)
(none)
BSC G400KS Computer 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 much 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 magnitudes larger than ever before (the rise of `big data`).
As a result of that new paradigms for storing, indexing and accessing information have emerged. This module will provide the essential foundations of information retrieval and equip the students with solid, applicable knowledge of state-of-the-art search technology. Students will write computer programs to solve IR tasks.
The aim of the module is to provide the essential foundations of information retrieval and equip the students with solid, applicable knowledge of state-of-the-art search technology.
On completion of the module, students will be expected to be able to:
1. Design and implement a standard information retrieval system
2. Understand standard IR models and their merits and limitations
3. Demonstrate practical knowledge of employing state-of-the-art open source software for IR
4. Demonstrate an understanding of commonly used evaluation approaches in IR
5. Understand advanced concepts of search applications
No additional information available.
Lectures, lab sessions and classes
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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.
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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.
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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.
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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.
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Mitra, B. and Craswell, N. (2018)
Introduction to Neural Information Retrieval. Hanover: now publishers Inc. Available at:
https://doi.org/10.1561/1500000061.
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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.
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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.
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Baeza-Yates, R. and Ribeiro-Neto, B. (2011) Modern information retrieval: the concepts and technology behind search. Second edition. Harlow: Pearson Addison-Wesley.
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Salton, G. (1989) Automatic Text Processing: The Transformation, Analysis, and Retrieval of Information by Computer. Addison-Wesley Publishing Company.
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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 |
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.
No
No
No
No external examiner information available for this module.
Available via Moodle
No lecture recording information available for this module.
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