CSC5024Z - Information Retrieval
12 credits at NQF level 9
Admission into the Master's degree specialising in Computer Science, or permission from the course convener. Basic understanding of XML data is required. Some background on statistics and linear algebra will be useful.
The objective is to understand how search engines work at an algorithmic level. Learn how to build and incorporate basic and specialized search engines into your own projects. Course content includes: Introduction to Information Retrieval (IR); Models of Basic IR (Boolean, Vector, Probabilistic); IR evaluation and testbeds; Stemming, Stopping, Relevance Feedback; Models of Web and linked-data retrieval (Pagerank, HITS); Latent Semantic Analysis and Clustering; Multimedia IR; Cross-lingual and multilingual IR; and IR in Practice (CMSes, digital libraries, Web, social media, etc.). Selected topics will be included from: Distributed and Federated IR; Recommender Systems; Natural Language Processing for IR; Sentiment Analysis; Opinion Retrieval; and Text Summarization.