Explores Latent Semantic Indexing in Information Retrieval, discussing algorithms, challenges in Vector Space Retrieval, and concept-focused retrieval methods.
Explores optimizing word embedding models, including loss function minimization and gradient descent, and introduces techniques like Fasttext and Byte Pair Encoding.
Explores document retrieval, classification, sentiment analysis, and topic detection in text analysis using supervised learning and bag-of-words models.
Introduces the basics of information retrieval, covering text-based retrieval, document features, similarity functions, and the difference between Boolean and ranked retrieval.
Explores algorithms and techniques for information extraction, including Viterbi algorithm, named entities recognition, and distant supervision.
Graph Chatbot
Chat with Graph Search
Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.
DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.