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Module Specifications..

Current Academic Year 2023 - 2024

Please note that this information is subject to change.

Module Title Mechanics of Search
Module Code CA6005I
School School of Computing
Module Co-ordinatorSemester 1: Cathal Gurrin
Semester 2: Cathal Gurrin
Autumn: Cathal Gurrin
Module TeachersCathal Gurrin
Denise Freir
Annalina Caputo
NFQ level 9 Credit Rating 7.5
Pre-requisite None
Co-requisite None
Compatibles None
Incompatibles None
Repeat examination

The aim of this module is to present the student with the technical background necessary to understand how to effectively develop information retrieval systems and forward-thinking strategies to analyse personal and online data to develop enhanced information access, support and communication strategies. The module will firstly provide a thorough grounding in the mechanics of how information access and retrieval systems operate. The student will be presented with the main theoretical models behind search engines to understand their main limitations and strengths. The module will then explore how to mine knowledge from multimedia and individual data to support next-generation content search, recommendation and personalisation. New devices and methods will be considered here also. The final section of the module explores new directions and challenges in the search and information access landscape. The student will finish the course with a solid understanding of search and personal data, and utilising this information to communicate with the individual.

Learning Outcomes

1. Understand the theory of Information Retrieval and appraise different retrieval models with their differences and similarities.
2. Understand the main components behind search engines, how they work together, how they differ when applied on the Web.
3. Illustrate the main components of a retrieval evaluation and design an experiment for a specific domain of utilisation.
4. Discuss the utilisation of ML in information retrieval and formulate a specific solution applied on a given context and domain.
5. Develop an understanding of the challenged posed by multimedia retrieval and develop specific solutions to tackle with multimedia content, such as image, audio and video.
6. Discuss the role of the user in an information retrieval system and debate the new role played in search engines by social media and personal data.
7. Formulate specific search solutions based on the exploitation of standard retrieval techniques and more advanced use of personal, social and sensory data.

Workload Full-time hours per semester
Type Hours Description
Directed learning36Online learning material on FutureLearn
Independent Study151No Description
Total Workload: 187

All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml

Indicative Content and Learning Activities

Assessment Breakdown
Continuous Assessment100% Examination Weight0%
Course Work Breakdown
TypeDescription% of totalAssessment Date
ProjectDesign and Implementation of a textual IR search engine This project assessment will require the student to design, develop and evaluate a desktop search engine by implementing VSM, BM25 and LM retrieval models. The student will also generate a report documenting the whole process explaining the pros/cons of each adopted choice. The student cannot make use of public available API for indexing and retrieval (such as Lucene, Solr, Indri, Lemure, MG4J, etc.). The student will be provided with a small reference text collection with which to do the experiments.50%Week 5
ProjectUsing an existing open-source search engine (e.g Lucene, Solr), implement a multimedia (image search engine) utilizing available metadata and existing APIs for automatic annotation, with appropriate user interface motivated by state-of-the-art multimedia interactive retrieval systems. The student will write a report and demonstrate their search engine.50%Week 10
Reassessment Requirement Type
Resit arrangements are explained by the following categories;
1 = A resit is available for all components of the module
2 = No resit is available for 100% continuous assessment module
3 = No resit is available for the continuous assessment component
This module is category 1
Indicative Reading List

  • Gurrin, Cathal , Smeaton, Alan F. and Doherty, Aiden R.: 2014, LifeLogging: personal big data, 1, Foundations and Trends in Information Retrieval, 1554-0677
Other Resources

Programme or List of Programmes
MCMM.Sc. in Computing
MCMECMicro-Credential Modules Eng & Comp
MCMVM.Sc. in Computing
SMPECSingle Module Programme (Eng & Comp)

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