Information Retrieval (IR) is an area that aims at answering user information needs with the most relevant information. In this course we shall study how process text and natural language data and extract information from it to support multiple text related tasks.
This course starts by dissecting a text processing pipeline, and discusses the fundamental techniques currently used in information retrieval and NLP. Afterwards, the most relevant retrieval models, ranking and categorization methods and question answering techniques are discussed in detail.
This course includes extensive hands-on laboratories where key retrieval and NLP algorithms are examined. The goal is to strengthen students’ experimental analysis and critical thinking skills concerning search performance metrics and experimental results.
Exam (40%) + Lab work (60% with three submissions)