Can I read An Introduction to Neural Information Retrieval t on EtoBox?

An Introduction to Neural Information Retrieval t by Bhaskar Mitra; Nick Craswell is a nonfiction available to read on EtoBox.

What is An Introduction to Neural Information Retrieval t about?

Neural ranking models for information retrieval (IR) use shallow or deep neural networks to rank search results in response to a query. Traditional learning to rank models employ supervised machine learning (ML) techniques-including neural networks-over hand-crafted IR features. By contrast, more recently proposed neural models learn representations of language from raw text that can bridge the gap between query and document vocabulary. Unlike classical learning to rank models and non-neural approaches to IR, these new ML techniques are data-hungry, requiring large scale training data before they can be deployed. This tutorial introduces basic concepts and intuitions behind neural IR models, and places them in the context of classical non-neural approaches to IR. We begin by introducing fundamental concepts of retrieval and different neural and non-neural approaches to unsupervised learning of vector representations of text. We then review IR methods that employ these pre-trained neural vector representations without learning the IR task end-to-end. We introduce the Learning to Rank (LTR) framework next, discussing standard loss functions for ranking. We follow that with an overvie

Who reads An Introduction to Neural Information Retrieval t?

Author

Bhaskar Mitra; Nick Craswell

Publisher

now Publishers Inc

Published

2018

Language

EN

ISBN

9781680835335

Category

nonfiction

Subjects

Technology, Science, Computer Science