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====== GINF533U - Information Access and Retrieval ====== Available from Master 2 [[http://mosig.imag.fr/ProgramEn/M2S1|MOSIG]] and [[https://iam.imag.fr/m2tracks#data_science_ds|MSIAM]]. [[http://ufrima.imag.fr/ue/WebFormation/ue.php?code=GINF533U&ismat=&lang=en|Course Description]] This course is given by [[http://mrim.imag.fr/User/jean-pierre.chevallet/|Jean-Pierre Chevallet]], [[http://lig-membres.imag.fr/mulhem/|Philippe Mulhem]] and [[http://lig-membres.imag.fr/quenot/|Georges Quénot]] from the [[http://lig-mrim.imag.fr/|Multimedia Information Modeling and Retrieval]] (MRIM) research group of the [[https://www.liglab.fr/en|Grenoble Informatics Laboratory]] (LIG). Contact: [[mailto:Georges.Quenot@imag.fr"|Georges.Quenot@imag.fr]] Part I. Foundations of Information Retrieval (Jean-Pierre Chevallet) * Course 1: {{ ::m2r_mosig_iar_2016_chapter_01_information_retrieval_basics.pdf |Information retrieval basics.}} * Course 2: {{ ::m2r_mosig_iar_chapter_02_classical_models_for_information_retrieval.pdf |Classical models for information retrieval.}} * Course 3: {{ ::probabilistic_information_retrieval.pdf |Probabilistic IR Models}} * Course 4: Natural language processing for information retrieval, Theoretical models for information retrieval. Part II: Web and social networks (Philippe Mulhem) * Course 5: {{ :web_ir.pdf |Web information retrieval}}. * Course 6: IR evaluation ({{ :evaluation_ir_-_mosig.pdf |classical}} and {{ ::ir_heuristics_-_mosig.pdf |axiomatic}}). * Course 7: {{ ::personnalization-social.pdf |Social networks Personalized for information retrieval}}. * Course 8: Recommender systems. Part III: Multimedia indexing and retrieval (Georges Quénot) * Course 9: {{ ::m2-mosig-iar-9.pdf |Visual content representation and retrieval}}. * Course 10: Classical machine Learning for multimedia indexing. * Course 11: Deep learning for information retrieval. * Course 12: Deep learning for multimedia indexing and retrieval. Reference to IR books or papers * [[http://nlp.stanford.edu/IR-book/|Introduction to Information Retrieval, http://nlp.stanford.edu/IR-book/]] * [[https://ciir.cs.umass.edu/irbook/|Search Engines Information Retrieval in Practice, https://ciir.cs.umass.edu/irbook/]]
