【文件属性】:
文件名称:Relevant.Search.With.applications.for.Solr.and.Elasticsearch
文件大小:14.44MB
文件格式:PDF
更新时间:2019-11-10 10:08:18
Solr Elastic Relevant Search
Summary
Relevant Search demystifies relevance work. Using Elasticsearch, it teaches you how to return engaging search results to your users, helping you understand and leverage the internals of Lucene-based search engines.
Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
About the Technology
Users are accustomed to and expect instant, relevant search results. To achieve this, you must master the search engine. Yet for many developers, relevance ranking is mysterious or confusing.
About the Book
Relevant Search demystifies the subject and shows you that a search engine is a programmable relevance framework. You'll learn how to apply Elasticsearch or Solr to your business's unique ranking problems. The book demonstrates how to program relevance and how to incorporate secondary data sources, taxonomies, text analytics, and personalization. In practice, a relevance framework requires softer skills as well, such as collaborating with stakeholders to discover the right relevance requirements for your business. By the end, you'll be able to achieve a virtuous cycle of provable, measurable relevance improvements over a search product's lifetime.
What's Inside
Techniques for debugging relevance?
Applying search engine features to real problems?
Using the user interface to guide searchers?
A systematic approach to relevance?
A business culture focused on improving search
About the Reader
For developers trying to build smarter search with Elasticsearch or Solr.
About the Authors
Doug Turnbull is lead relevance consultant at OpenSource Connections, where he frequently speaks and blogs. John Berryman is a data engineer at Eventbrite, where he specializes in recommendations and search.
Foreword author, Trey Grainger, is a director of engineering at CareerBuilder and author of Solr in Action.
Table of Contents
Chapter 1 The search relevance problem
Chapter 2 Search—under the hood
Chapter 3 Debugging your first relevance problem
Chapter 4 Taming tokens
Chapter 5 Basic multifield search
Chapter 6 Term-centric search
Chapter 7 Shaping the relevance function
Chapter 8 Providing relevance feedback
Chapter 9 Designing a relevance-focused search application
Chapter 10 The relevance-centered enterprise
Chapter 11 Semantic and personalized search
Appendix A Indexing directly from TMDB
Appendix B Solr reader’s companion
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