探索Elasticsearch与Solr的实用搜索相关技术

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《相关搜索：Solr与Elasticsearch的应用指南》是一本深入解析搜索引擎中相关性工作原理的专业书籍，由 Doug Turnbull 和 John Berryman 联合撰写，Trey Grainger 出任序言作者。本书主要针对希望利用 Elasticsearch 或 Solr 建立智能搜索的开发者，帮助他们理解并掌握基于 Lucene 的搜索引擎内部机制，以提供更吸引用户的搜索结果。书中首先介绍搜索相关性的核心问题，阐述了用户对于即时、相关搜索结果的期待。作者强调，开发人员需要掌握如何编程实现相关性，以及如何整合二次数据源、分类体系、文本分析和个人化等因素，确保搜索结果符合业务需求。书中的内容包括： 1. **搜索引擎底层工作原理**：揭示搜索引擎的工作机制，让读者对索引和搜索算法有深入理解。 2. **调试相关性问题**：提供实用技巧，帮助开发者诊断和解决在实现相关性时遇到的问题。 3. **处理分词与多字段搜索**：讲解如何优化关键词匹配，以及在不同字段间灵活搜索。 4. **术语为中心的搜索**：探讨基于关键词的搜索策略，提升搜索精准度。 5. **塑造和调整相关性函数**：通过实例演示如何设计个性化和动态的相关性权重。 6. **获取反馈和迭代改进**：教授如何收集用户反馈，持续优化搜索体验。 7. **设计以相关性为核心的搜索应用**：指导开发者创建用户友好的搜索界面，引导用户发现所需信息。 8. **企业级的相关性中心化**：讨论将相关性搜索融入企业整体战略的重要性。 9. **语义和个性化搜索**：探索如何利用自然语言处理和用户行为数据实现更深层次的搜索定制。此外，书中还提供了两个实用附录，分别是直接从 TMDB 索引的示例以及 Solr 的配套阅读指南，以便读者更好地实践和学习。《相关搜索：Solr与Elasticsearch的应用指南》不仅是一本技术手册，也是一部引导开发者建立良好企业搜索文化的指南，旨在推动搜索产品的持续改进和性能提升。购买纸质版书籍会附赠电子版（PDF、Kindle 和 ePub 格式），并且读者可访问 Manning Publications 官网获取更多信息或享受团体购买优惠。

preface

John and I met while working together as consultants for OpenSource Connections

(OSC) solving tough search problems for clients. Sometimes we triaged perfor-

mance (make it go faster!). Other times we helped build out a search application.

All of these projects had simple-to-measure success metrics. Did it go faster? Is the

application complete?

Search relevance, though, doesn’t play by these rules. And users, raised in the age

of Google, won’t tolerate “good enough” search. They want “damn smart” search. They

want search to prioritize criteria they care about, not what the search engine often

idiotically guesses relevant.

Like moths attracted to a flame, we both felt drawn to this hard problem. And just

like said moths, we often found ourselves burned. Through these painful lessons, we

persevered and grew, succeeding at tasks we initially considered too difficult.

During this time, we also found our voices on OSC’s blog. We realized that little

was being written about search relevance problems. We developed ideas such as test-

driven relevancy. We documented our headaches, our problems, and our triumphs.

Together we experimented with machine learning approaches, like latent semantic

analysis. We dove into Lucene’s guts and explored techniques for building custom

search components to solve problems. We began exploring information retrieval

research. As we learned more techniques to solve hard problems, we continued to

write about them.

Still, blogs have their limits. John and I always hoped to express our ideas more

systematically in book form. Luckily, we experienced one of those funny chains of

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探索Elasticsearch与Solr的实用搜索相关技术

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