提升搜索引擎效果:Solr和Elasticsearch深度定制指南

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"Relevant Search: 掌握搜索引擎的艺术" 《Relevant Search》是一本专为Solr和Elasticsearch开发者编写的指南,旨在帮助他们理解并优化用户搜索体验。该书深入探讨了如何根据自己的需求精确控制搜索结果排名,而非完全依赖搜索引擎的算法。作者针对这两种流行的全文搜索引擎提供了定制化索引和排名策略的方法,让开发人员能够更好地理解“相关性”在自己应用中的实际意义。 这本书特别适合那些对现有搜索引擎感到困惑,希望提升搜索效果的开发者。即使读者对基础搜索引擎操作有所了解,也能通过本书进一步提升技术技能。内容不仅涵盖了技术层面,还从组织架构、产品策略、营销以及领域专家的角度出发,阐述了如何从整体上优化搜索体验。 书中涉及的关键知识点包括: 1. Solr和Lucene技术:作为基础,Solr是基于Apache Lucene的开源全文搜索平台,而Lucene提供了一种强大的搜索库,用于构建高效检索系统。《Relevant Search》将深入讲解如何利用这些工具实现更精准的搜索结果排序。 2. Elasticsearch:作为另一个主流的分布式搜索解决方案,Elasticsearch提供了实时搜索、分析和聚合功能。书中会介绍如何在Elasticsearch中调整和优化搜索算法,确保与用户需求的紧密契合。 3. Relevance Ranking:核心主题是如何构建自定义的搜索排名算法,这涉及到查询解析、权重分配、关键词匹配和文档特征提取等多个环节。读者可以学习到如何根据业务场景和用户行为调整相关性模型。 4. 实践案例与方法:书中提供了一系列实际案例和步骤,指导读者如何在项目中实施相关搜索策略,包括数据预处理、索引结构调整、查询参数优化等。 5. 产品策略视角:《Relevant Search》强调了产品管理、内容策略、市场营销和领域专家在搜索优化中的角色,帮助读者从更高的层面上思考搜索功能的价值和影响。 6. 版权和获取方式:最后,书中的版权信息提醒读者关于复制和传播的注意事项,并给出了Manning Publications的购买和联系信息,以及订购折扣的相关细节。 《Relevant Search》是一本结合技术深度和商业洞察的实用手册,对于希望在Solr和Elasticsearch上打造卓越搜索体验的开发者来说,它是一份不可或缺的参考资料。无论是技术新手还是经验丰富的专家,都可以从中找到提升搜索质量的方法和策略。
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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