Chapter 1. The search relevance problem

This chapter covers

  • The ubiquity of search (search is all around us!)
  • The challenge of building a relevant search experience
  • Examples of this challenge for prominent search domains
  • The inability of out-of-the-box solutions to solve the problem
  • This book’s approach for building relevant search

Getting a search engine to behave can be maddening. Whether you’re just getting started with Solr or Elasticsearch, or you have years of experience, you’ve likely struggled with low-quality search results. Out-of-the-box settings haven’t met your needs, and you’ve fought to deliver even marginally relevant search results.

When it comes to relevance ranking, a search engine can seem like a mystical black box. It’s tempting to ignore relevance problems—turning the focus away from search and toward other, less mystical parts of the application such as performance or the UI. Unfortunately, the work of search relevance ranking can’t be avoided. Users increasingly need to work with large amounts of content in today’s applications. Whether this means products, books, log messages, emails, vacation rentals, or medical articles—the search box is the first place your users go to explore and find answers. Without intuitive search to answer questions in human terms, they’ll be hopelessly lost. Thus, despite the maddening, seemingly mystical nature of search, you have to find solutions.

1.1. Your goal: gaining the skills of a relevance engineer

1.2. Why is search relevance so hard?

1.3. Gaining insight from relevance research

1.4. How do you solve relevance?

1.5. More than technology: curation, collaboration, and feedback

1.6. Summary

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