Mechanics of Search

The aim of this microcredential is to present the student with the technical background necessary to understand how to effectively develop information retrieval systems and forward-thinking strategies. The student will learn to use these valuable skills 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 extract 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.

1. To understand the theory of Information Retrieval and review different retrieval models with their differences and similarities.
2. To understand the main components behind search engines, how they work together, how they differ when applied on the Web.
3. To illustrate the main components of a retrieval evaluation and design an experiment for a specific domain of utilisation.
4. To discuss the utilisation of ML in information retrieval and prepare a specific solution applied on a given context and domain.
5. To develop an understanding of the challenges posed by multimedia retrieval and develop specific solutions to tackle multimedia content, such as image, audio and video.
6. To 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. To come up with specific search solutions based on the exploitation of standard retrieval techniques and more advanced use of personal, social and sensory data.