Mr Ammar Naich

Teaching

Information Retrieval (Undergraduate)

The field of information retrieval (IR) aims to provide techniques and tools to support effective and efficient access to large amounts of textual information (e.g. stored on the web, digital libraries, intranets). This involves representation, retrieval, presentation and user issues. The following topics will be covered: 1. Application of representation and retrieval approaches described in the Foundations of Information Retrieval module, Semester A, in the context of structured documents, in particular web documents, and digital libraries. 2. Databases & information retrieval, and logical models for information retrieval. 3. The organisation of documents according to categories (e.g. Yahoo directory) or their content to provide more effective presentation of the collection to the users. 4. The design of interfaces and visualisation tools that aim at supporting end-users in their search tasks. 5. User aspects, including the evaluation of IR systems according to user satisfaction, and the incorporation of user information seeking behaviour in the search task. The module consists of 3 hours per week of lectures for 12 weeks, including labs and tutorials.

Information Retrieval (Postgraduate)

The field of information retrieval (IR) aims to provide techniques and tools to support effective and efficient access to large amounts of textual information (e.g. stored on the web, digital libraries, intranets). This module will describe the IR field in details, both its theoretical and empirical aspects. The following topics will be covered: Indexing: Representing the information content of documents through the use of e.g. stop word removal, stemming, and term weight calculation. Retrieval: Building models that select which information objects are relevant to a user''s need. Models will include Boolean model, vector space model, probabilistic model, language model, inference network model, and relevance feedback model. Evaluation: Implementing and evaluating IR models, mainly with respect to effectiveness aspects. The course consists of 3 hours per week of lectures for 12 weeks, including labs and tutorials. Labs will make use of the HySpirit, a state-of-the-art IR experimental platform to design and implement indexing and retrieval strategies.

Machine Learning (Postgraduate)

The aim of the module is to give students an understanding of machine learning methods, including pattern recognition, clustering and neural networks, and to allow them to apply such methods in a range of areas.

Software Engineering Project (Undergraduate)

Students in pre-assigned groups of approximately six will be presented with a significant software problem to solve. To meet the problem requirements and build a satisfactory system within the time constraints the students will have to apply the principles learnt in the Software Engineering module and will have to work effectively as a team. Each team must choose a project manager and assign appropriate roles to each member.

Research