Summary Solr in Action is a comprehensive guide to implementing scalable search using Apache Solr. This clearly written book walks you through well-documented examples ranging from basic keyword searching to scaling a system for billions of documents and queries. It will give you a deep understanding of how to implement core Solr capabilities. About the Book Whether you're handling big (or small) data, managing documents, or building a website, it is important to be able to quickly search through your content and discover meaning in it. Apache Solr is your tool: a ready-to-deploy, Lucene-based, open source, full-text search engine. Solr can scale across many servers to enable real-time queries and data analytics across billions of documents. Solr in Action teaches you to implement scalable search using Apache Solr. This easy-to-read guide balances conceptual discussions with practical examples to show you how to implement all of Solr's core capabilities. You'll master topics like text analysis, faceted search, hit highlighting, result grouping, query suggestions, multilingual search, advanced geospatial and data operations, and relevancy tuning. This book assumes basic knowledge of Java and standard database technology. No prior knowledge of Solr or Lucene is required. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. What's Inside <ul>
<li>How to scale Solr for big data</li>
<li>Rich real-world examples</li>
<li>Solr as a NoSQL data store</li>
<li>Advanced multilingual, data, and relevancy tricks</li>
<li>Coverage of versions through Solr 4.7</li>
</ul>
 About the Authors Trey Grainger is a director of engineering at CareerBuilder. Timothy Potter is a senior member of the engineering team at LucidWorks. The authors work on the scalability and reliability of Solr, as well as on recommendation engine and big data analytics technologies. Table of Contents <ol>PART 1 MEET SOLR<li>Introduction to Solr</li>
<li>Getting to know Solr </li>
<li>Key Solr concepts </li>
<li>Configuring Solr </li>
<li>Indexing </li>
<li>Text analysis </li>PART 2 CORE SOLR CAPABILITIES<li>Performing queries and handling results</li>
<li>Faceted search</li>
<li>Hit highlighting</li>
<li>Query suggestions</li>
<li>Result grouping/field collapsing</li>
<li>Taking Solr to production</li>PART 3 TAKING SOLR TO THE NEXT LEVEL<li>SolrCloud</li>
<li>Multilingual search</li>
<li>Complex query operations</li>
<li>Mastering relevancy</li>
</ol>

Solr in Action

Computers & Technology

Grainger, Trey

Potter, Timothy

Web Development & Design

Manning

AI-Powered Search teaches you the latest machine learning techniques to create search engines that continuously learn from your users and your content, to drive more domain-aware and intelligent search.\nGreat search is all about delivering the right results. Today’s search engines are expected to be smart, understanding the nuances of natural language queries, as well as each user’s preferences and context. AI-Powered Search teaches you the latest machine learning techniques to create search engines that continuously learn from your users and your content, to drive more domain-aware and intelligent search. 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 the hidden semantic relationships in your content to constantly get smarter and automatically deliver better, more relevant search experiences.\nPurchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.\nAbout the technology 
The search box has become the de facto user interface for modern data-driven applications. Users expect software to fully understand their search inputs, context, and activity, and to 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.\nAbout the book 
AI-Powered Search is an authoritative guide to applying leading-edge data science techniques to search. It teaches you how to build search engines that automatically understand the intention of a query in order to deliver significantly better results. Author Trey Grainger helped develop numerous algorithms now transforming search, and is an expert on leading techniques for crowdsourced relevancy and semantic search. Working through code in interactive notebooks, you’ll deploy intelligent search systems that deliver real-time personalization and contextual understanding of each user, domain, and query through a self-learning search platform that can tune its own results automatically.\nWhat's inside 
Using 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 Personalized search utilizing user behavioral 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 reader 
For software developers or data scientists familiar with the basics of search engine development.\nAbout 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.

AI-Powered Search

Turnbull, Doug

Irwin, Max

Computer Science

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