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Lectures
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Lecture 1: Introduction to IR
Lecture 2: Boolean Retrieval & Inverted Index
Lecture 3: Data Structures & Tolerant Retrieval
Lecture 4: Term Weighting & Vector Space Model
Lecture 4: VSM (recording of the online session)
Lecture 5: Classic Probabilistic Retrieval
Lecture 6: Language Modeling for Information Retrieval
Lecture 7: Relevance Feedback & Query Expansion
Lecture 8: Latent & Semantic Retrieval
Lecture 9: Classification, Clustering and Learning to Rank
Lecture 9: Classification, Clustering, and Learning to Rank (online lecture recording)
Lecture 10: Neural Learning to Rank
Lecture 11: IR Evaluation
Lecture 12: Link Analysis in Web Search
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Exercise 01
Exercise 01 - Solution
Projects - Intro
Exercise 02
Exercise 02 - Solutions
Exercise 03 - Relevance Feedback & Semantic Retrieval
Exercise 03 - Solutions
Exercise 04 - Machine Learning, Evaluation & PageRank
Exercise 04 - Solutions
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Results of the second exam (11.10.2023)
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Sommersemester 2023
Master- und Aufbaustudiengänge
SS23_mNLP
Exams
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Kursbeschreibung
Multilingual and advanced natural language processing (NLP) (prior NLP experience desirable, e.g., attendance of the course "Sprachverarbeitung & Text Mining" or "Machine Learning for NLP", but not necessary)
Lehrende
Benedikt Ebing
Goran Glavaš
Fabian Schmidt
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Select activity Exam Results (Klausur, 20.7.2023)
Exam Results (Klausur, 20.7.2023)
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