Module Database Search



MODULE DESCRIPTOR
Module Title
Information Retrieval
Reference CM4144 Version 1
Created January 2024 SCQF Level SCQF 10
Approved April 2024 SCQF Points 15
Amended ECTS Points 7.5

Aims of Module
To provide students with a comprehensive understanding of the main principles and practices underlying the retrieval, extraction and mining of text and other data using advanced analytical techniques, including recommender systems, to make business decisions.

Learning Outcomes for Module
On completion of this module, students are expected to be able to:
1 Examine the main concepts involved in information retrieval.
2 Develop intelligent information retrieval systems.
3 Test the effectiveness of information retrieval systems.
4 Execute state-of-the-art techniques for web mining and natural language processing.
5 Develop a recommender system for a given purpose.

Indicative Module Content
Information collection: crawling and document pre-processing. Information retrieval: document Indexing, similarity metrics and clustering. Web Analytics. Comparative analysis of information retrieval and visualisation methods. Text extraction, tokenisation, stemming, bag-of-words, n-gram, statistical language models, vector representations and topic models. Word sense disambiguation, phrase and named entity recognition, POS tagging, shallow parsing, syntax and dependency parsing. Document similarity, clustering and classification, information extraction, sentiment analysis using lexicon-based techniques. Case studies on text classification, topic modelling applied to news articles, intelligent search and browse, social media mining. Personalisation, recommendation, user modelling, and interactive smart information systems.

Module Delivery
Lectures are used to deliver the main principles and techniques. Computing laboratories will be used to acquire and practise practical skills and reinforce knowledge from the lectures.

Indicative Student Workload Full Time Part Time
Contact Hours 30 N/A
Non-Contact Hours 120 N/A
Placement/Work-Based Learning Experience [Notional] Hours N/A N/A
TOTAL 150 N/A
Actual Placement hours for professional, statutory or regulatory body    

ASSESSMENT PLAN
If a major/minor model is used and box is ticked, % weightings below are indicative only.
Component 1
Type: Practical Exam Weighting: 100% Outcomes Assessed: 1, 2, 3, 4, 5
Description: A practical exam assessing knowledge and practical skills in information retrieval techniques and evaluation of their results.

MODULE PERFORMANCE DESCRIPTOR
Explanatory Text
The calculation of the overall grade for this module is based on 100% weighting of Component 1. To pass the module students should achieve grade D or better.
Module Grade Minimum Requirements to achieve Module Grade:
A The student must achieve an A in C1.
B The student must achieve a B in C1.
C The student must achieve a C in C1.
D The student must achieve a D in C1.
E The student must achieve an E in C1.
F The student must achieve an F in C1.
NS Non-submission of work by published deadline or non-attendance for examination

Module Requirements
Prerequisites for Module None.
Corequisites for module None.
Precluded Modules None.

INDICATIVE BIBLIOGRAPHY
1 Web information retrieval. Ceri, Stefano, 2013
2 Designing the search experience : the information architecture of discovery. Russell-Rose, Tony.; Tate, Tyler. 2013
3 Information Retrieval Searching in the 21st Century. Goker, Ayse and Davies, John. 2009
4 Artificial intelligence a modern approach. Russell, Stuart J. , Norvig, Peter, 2014.
5 Recommendation and search in social networks. Ulusoy, Ozgur, Tansel, Abdullah Uz, Arkun, Erol, 2015.

Robert Gordon University, Garthdee House, Aberdeen, AB10 7QB, Scotland, UK: a Scottish charity, registration No. SC013781