Neural Networks for Information Retrieval
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.
Cite
@article{arxiv.1707.04242,
title = {Neural Networks for Information Retrieval},
author = {Tom Kenter and Alexey Borisov and Christophe Van Gysel and Mostafa Dehghani and Maarten de Rijke and Bhaskar Mitra},
journal= {arXiv preprint arXiv:1707.04242},
year = {2017}
}
Comments
Overview of full-day tutorial at SIGIR 2017