Are you an EPFL student looking for a semester project?
Work with us on data science and visualisation projects, and deploy your project as an app on top of Graph Search.
This lecture covers the fundamentals of Information Retrieval (IR), including the vector space model, indexing terms, weighting schemes like tf.idf and Okapi BM25, cosine proximity measure, representing queries, and evaluating IR systems. It delves into the limitations of the vector space model, distributional semantics, and advanced models. Key topics include tokenization, filtering, Bag of Words model, and the importance of good indexing for IR system performance.
This video is available exclusively on Mediaspace for a restricted audience. Please log in to MediaSpace to access it if you have the necessary permissions.
Watch on Mediaspace