We will be giving a full day tutorial on "Neural Networks for Information Retrieval", with Tom Kenter, Alexey Borisov, Christophe Van Gysel, Maarten de Rijke, Bhaskar Mitra at The 40th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR2017). \o/
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. It is structured as follows:
- Basic concepts:
- Main concepts involved in neural systems will be covered, such as back propagation, distributed representations/embeddings, convolutional layers, recurrent networks, sequence-to-sequence models, dropout, loss functions, optimization schemes like Adam.
- Semantic matching:
- Different methods for supervised, semi- and unsupervised learning for semantic matching will be discussed.
- Learning to Rank with Neural Networks:
- Feature-based models for representation learning, ranking objectives and loss functions, and training a neural ranker under different levels of supervision are going to be discussed.
- Modeling user behavior with Neural Networks:
- Probabilistic graphical models, Neural click models, and modeling biases using neural network will be described.
- Generating Models:
- The ideas on machine reading task, question answering, conversational IR, and dialogue systems will be covered.
hummm...got existed? Join us at SIGIR2017 🙂
The material from our SIGIR 2017 tutorial on Neural Networks for Information Retrieval (NN4IR) is available online at http://nn4ir.com.