AI-Powered Search

by Trey Grainger, Doug Turnbull, Max Irwin

Overview

Learn everything about the latest machine learning techniques and create search engines that drive more domain-aware and intelligent search.

AI-Powered Search teaches you the latest machine-learning techniques to create search engines that continuously learn from your users and your content. Written by Trey Grainger, the Chief Algorithms Officer at Lucidworks, this authoritative book empowers you to create and deploy search engines that take advantage of user interactions and hidden semantic relationships.

This book is ideal for software developers or data scientists familiar with the basics of search engine development. It will show you ways to create content that will constantly get smarter and automatically deliver better, more relevant search experiences.

What''s inside

• Reflected intelligence to continually learn and improve search relevancy
• Natural language search with automatically-learned knowledge graphs
• Semantic search, with domain-specific terms, phrases, concepts, and relationships
• Personalised search, utilising user behavioural signals and learned user profiles
• Automated Learning to Rank (machine-learned ranking) from user signals
• Word embeddings, vector search, question answering, image and voice search, and other modern search paradigms

About the technology

The search box has become the "de facto" user interface for modern data-driven applications. Users expect the software to fully understand their search inputs, context, and activity and return the right answers, every time. Fortunately, you no longer need a massive team manually adjusting relevancy parameters to deliver optimal search results. Using the power of AI, you can develop search solutions that dynamically learn from your content and users, constantly getting smarter and delivering better answers.

Product Details

ISBN-13:	9781617296970
Publisher:	Manning
Publication date:	01/28/2025
Pages:	520
Product dimensions:	7.38(w) x 9.25(h) x 1.10(d)

About the Author

Trey Grainger is the Chief Algorithms Officer at Lucidworks, the AI-powered search company that powers hundreds of the world’s leading organizations. Trey co-authored Solr in Action and has over 12 years experience building semantic search engines, recommendation engines, real-time analytics systems, and leading related engineering and data science teams.

Doug Turnbull is Staff Relevance Engineer at Spotify and is the former Chief Technical Officer at OpenSource Connections. He is the co-author of the book Relevant Search, and contributed chapters 10-12 on “Learning to Rank”, “Automated Learning to Rank with Click Models”, and “Overcoming Bias in Learned Relevance Models”.

Max Irwin is a Managing Consultant at OpenSource Connections, a leading search relevance consultancy. Max contributed chapters 13-14 on “Semantic Search with Dense Vectors” and “Question Answering and the Search Frontier”.