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Neural Networks for Information Retrieval (1707.04242v1)

Published 13 Jul 2017 in cs.IR, cs.AI, and cs.CL

Abstract: Machine learning plays a role in many aspects of modern IR systems, and deep learning is applied in all of them. The fast pace of modern-day research has given rise to many different approaches for many different IR problems. The amount of information available can be overwhelming both for junior students and for experienced researchers looking for new research topics and directions. Additionally, it is interesting to see what key insights into IR problems the new technologies are able to give us. The aim of this full-day tutorial is to give a clear overview of current tried-and-trusted neural methods in IR and how they benefit IR research. It covers key architectures, as well as the most promising future directions.

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Authors (6)
  1. Tom Kenter (9 papers)
  2. Alexey Borisov (5 papers)
  3. Christophe Van Gysel (24 papers)
  4. Mostafa Dehghani (64 papers)
  5. Maarten de Rijke (263 papers)
  6. Bhaskar Mitra (78 papers)
Citations (2)