| Module Title |
Search Technologies |
| Module Code |
CSC1103 (ITS: CA4009) |
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Faculty |
Computing |
School |
Engineering & Computing |
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NFQ level |
8 |
Credit Rating |
7.5 |
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Description
The use of search technologies to locate relevant information from within increasingly voluminous archives of online digital media is rapidly becoming a ubiquitous and vital technology for daily life both in social and working environments. These archives include formally published text materials, heterogeneous web content, social media, audio-visual content, and various forms of enterprise content. The efficient location and delivery of content from these archives is enabling many exciting opportunities, increasing social engagement, creative exploitation of information, improved efficiency in business operations. However, realizing systems to perform reliable search and discovery of information, and effective delivery to users poses many challenges.
This module introduces relevant search technologies and explores applications such as web search, image and video search, enterprise search and mobile search applications. The module covers key search topics, including content indexing, file structures, algorithms to support retrieval; related technologies such as content summarisation, speech and video processing; and user interaction in search and evaluation of search systems.
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Learning Outcomes
1. Explain the process of content indexing in information retrieval including stop word removal, conflation (stemming, string-comparison), and the language dependency of these methods.
2. 1DCDF71D-B347-0001-E09A-A62216ED19BF
3. Describe the need for indexing in multimedia content including spoken and visual content, including explaining the impact of recognition errors on information retrieval behaviour.
4. 1DCDF827-9CE5-0001-8F18-ACC469101750
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| Workload | Full time hours per semester | | Type | Hours | Description |
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| Lecture | 24 | Lectures will present the core material from the module. | | Laboratory | 12 | Students will undertaken structured laboratory examining key elements of indexing, search and evaluation. | | Tutorial | 12 | Students will be given practical guidance on use implementation and evaluation of their research project. | | Assignment Completion | 48 | Students will work on completing and writing up individual laboratory exercises, and undertaking group project. | | Independent Study | 91.5 | Students will study course material and prepare for the final examination. |
| Total Workload: 187.5 |
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| Section Breakdown | | CRN | 10604 | Part of Term | Semester 1 | | Coursework | 0% | Examination Weight | 0% | | Grade Scale | 40PASS | Pass Both Elements | Y | | Resit Category | RC1 | Best Mark | N | | Module Co-ordinator | Gareth Jones | Module Teacher | |
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| Assessment Breakdown |
| Type | Description | % of total | Assessment Date |
|---|
| Laboratory Portfolio | Undertake a series of individual laboratory exercises using a standard information retrieval toolkit to explore the operation of the indexing process, ranking models in information retrieval, relevance feedback, summary generation, and information retrieval evaluation for a small information retrieval test collection using standard evaluation metrics. | 15% | Week 25 | | Project | A research-style group project developing a simple novel information retrieval application. Project based on module material, but also taking in private research, with documentation of the design of the proposed application, and the evaluation of its search effectiveness using information retrieval evaluation methods. Students will be provided formative feedback on their project proposal in an assessed formative presentation. Assessment will be based on a group written report and group presentation. | 15% | Sem 2 End | | Formal Examination | End-of-Semester Final Examination | 70% | End-of-Semester |
| Reassessment Requirement Type |
Resit arrangements are explained by the following categories;
RC1: A resit is available for both* components of the module.
RC2: No resit is available for a 100% coursework module.
RC3: No resit is available for the coursework component where there is a coursework and summative examination element.
* ‘Both’ is used in the context of the module having a coursework/summative examination split; where the module is 100% coursework, there will also be a resit of the assessment
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Pre-requisite |
a,
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Co-requisite |
None |
| Compatibles |
None |
| Incompatibles |
None |
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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
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Indicative Content and Learning Activities
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Indicative Reading List
Books:
- Christopher D. Manning, Prabhakar Raghavan, Hinrich Schutze:: 2008, Introduction to information retrieval, 1, Cambridge University Press, 506, 978-0521865715
- Ricardo Baeza-Yates, Berthier Ribeiro-Neto: 2010, Modern Information Retrieval: The Concepts and Technology Behind Search, 2, Addison Wesley, 944, 978-0321416919
- Peter Jackson, Isabelle Moulinier: 2007, Natural Language Processing for Online Applications: Text Retrieval, Extraction, and Categorization, 2, John Benjamins Publishing Company, 247, 978-9027249920
Articles:
None |
Other Resources
None |
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