Latest Module Specifications
Current Academic Year 2025 - 2026
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Description This module is divided into 5 themes, namely Human Cognition and Information Seeking, Sensing People and Sensing Context, Search Mechanics and AI, Media Analysis and Machine Learning, and Semantic Web/Linked Data. The aim of the module is to familiariase students with a range of information seeking activities we pursue as part of day-to-day life and how Ai techniques are used in these information seeking activities. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Learning Outcomes 1. Analyse methods by which how human cognition, memory, and work/leisure tasks use computational support 2. Compare a variety of technologies for sensing human activities, including biometrics, and how AI techniques turn this into useful information 3. Understand and compare how search mechanisms, including web search, question answering, information retrieval, and recommender systems operate including how machine learning is used 4. Analyse how multimedia information, covering image and video, can be automatically deconstructed, analysed and understood using AI techniques 5. Understand how linked data and semantic web technologies operate and are used and be able to apply this in implementations. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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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
The module is delivered using the FutureLearn platform and is divided into 5 themes, each hosted on a separate MOOC, as 1. human cognition, how the human memory works, how we remember and forget, and how a variety of work/leisure tasks that we perform daily benefit from the use of computational support 2. a variety of technologies for sensing human activities, behaviour, location, including biometrics (HR, RR, GSR, EEG), and how AI techniques and in particular how machine learning turns this into useful information 3. search mechanisms, including basic information retrieval, word stemming, inverted files, and them moving on to web search, PageRank, PANDA, positive and negative weighting factors. The theme also covers question answering, and how recommender systems operate including how machine learning is used to learn profiles and learning-to-rank 4. how multimedia information, covering image and video, can be analysed and understood using AI techniques. This includes convolutional neural networks, ImageNet, TRECvid and how this is now used in systems like FaceBook 5. linked data and semantic web technologies, how they operate and how they are used. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Indicative Reading List Books: None Articles: None | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Other Resources None | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||