Deep Learning for Search teaches you how to improve the effectiveness of your search by implementing neural network-based techniques. By the time you're finished with the book, you'll be ready to build amazing search engines that deliver the results your users need and that get better as time goes on!
Foreword by Chris Mattmann.
About the Technology
Deep learning handles the toughest search challenges, including imprecise search terms, badly indexed data, and retrieving images with minimal metadata. And, with modern tools like DL4J and TensorFlow, you can apply powerful DL techniques without a deep background in data science or natural language processing (NLP). This book will show you how.
About the Book
Deep Learning for Search teaches you to improve your search results with neural networks. You'll review how DL relates to search basics like indexing and ranking. Then, you'll walk through in-depth examples to upgrade your search with DL techniques using Apache Lucene and Deeplearning4j. As the book progresses, you'll explore advanced topics like searching through images, translating user queries, and designing search engines that improve as they learn!
What's inside
• Accurate and relevant rankings • Searching across languages • Content-based image search • Search with recommendations
About the Reader
For developers comfortable with Java or a similar language and search basics. No experience with deep learning or NLP needed.
Table of Contents
PART 1 - SEARCH MEETS DEEP LEARNING • Neural search • Generating synonyms PART 2 - THROWING NEURAL NETS AT A SEARCH ENGINE • From plain retrieval to text generation • More-sensitive query suggestions • Ranking search results with word embeddings • Document embeddings for rankings and recommendations PART 3 - ONE STEP BEYOND • Searching across languages • Content-based image search • A peek at performance
