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