Georgetown University

Information retrieval is the identification of textual components, be them web pages, blogs, microblogs, documents, medical transcriptions, mobile data, or other big data elements, relevant to the needs of the user.  Relevancy is determined either as a global absolute or within a given context or view point.   Practical, but yet theoretically grounded, foundational and advanced algorithms needed to identify such relevant components are taught.  
The Information-retrieval techniques and theory, covering both effectiveness and run-time performance of information-retrieval systems are covered. The focus is on algorithms and heuristics used to find textual components relevant to the user request and to find them fast. The course covers the architecture and components of the search engines such as parser, index builder, and query processor. In doing this, various retrieval models, relevance ranking, evaluation methodologies, and efficiency considerations will be covered. The students learn the  material by building a prototype of such a search engine.  These approaches are in daily use by all search and social media companies.