Download Relevant Search: With applications for Solr and by Doug Turnbull PDF

By Doug Turnbull


Relevant Search demystifies relevance paintings. utilizing Elasticsearch, it teaches you the way to come enticing seek effects in your clients, aiding and leverage the internals of Lucene-based seek engines.

Purchase of the print e-book contains a loose book in PDF, Kindle, and ePub codecs from Manning Publications.

About the Technology

Users are familiar with and anticipate fast, suitable seek effects. to accomplish this, you need to grasp the hunt engine. but for plenty of builders, relevance score is mysterious or complicated.

About the Book

Relevant Search demystifies the topic and indicates you seek engine is a programmable relevance framework. you will find out how to follow Elasticsearch or Solr for your business's particular score difficulties. The publication demonstrates the way to application relevance and the way to include secondary facts resources, taxonomies, textual content analytics, and personalization. In perform, a relevance framework calls for softer abilities to boot, similar to participating with stakeholders to find the appropriate relevance requisites in your company. by way of the tip, it is easy to in achieving a virtuous cycle of provable, measurable relevance advancements over a seek product's lifetime.

What's Inside

  • Techniques for debugging relevance?
  • Applying seek engine good points to genuine problems?
  • Using the consumer interface to lead searchers?
  • A systematic method of relevance?
  • A enterprise tradition considering enhancing search

About the Reader

For builders attempting to construct smarter seek with Elasticsearch or Solr.

About the Authors

Doug Turnbull is lead relevance advisor at OpenSource Connections, the place he often speaks and blogs. John Berryman is an information engineer at Eventbrite, the place he makes a speciality of strategies and search.

Foreword writer, Trey Grainger, is a director of engineering at CareerBuilder and writer of Solr in Action.

Table of Contents

  1. The seek relevance challenge
  2. Search below the hood
  3. Debugging your first relevance challenge
  4. Taming tokens
  5. Basic multifield seek
  6. Term-centric seek
  7. Shaping the relevance functionality
  8. Providing relevance suggestions
  9. Designing a relevance-focused seek application
  10. The relevance-centered company
  11. Semantic and customized search

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Extra info for Relevant Search: With applications for Solr and Elasticsearch

Example text

Doc frequency is useful in document scoring because it establishes a notion of importance for a particular term. For instance, the term “the” typically has a high document frequency, which indicates that it carries little discriminatory value when determining the relevancy of a document for a given search. Term frequency The number of times that a term occurs in a particular document. 3, the term frequency for “shoe” in document 0 is 4, and the term frequency for “shoe” in document 1 is 2. Term frequency is useful in document scoring because it establishes a notion of how important a document is for a given term.

Content makes its way into the search engine, and users query and explore by interacting with a search application. Before getting under the hood, into the arcane black box, let’s quickly review the search engine’s capabilities from an outsider’s point of view. 1 A simple model of a search engine based on possible interactions 18 CHAPTER 2 Search—under the hood functions of a search engine are storing, finding, and retrieving content. Although these are all basic concepts, it’s useful to review them in order to establish a shared set of definitions and fill in any technical gaps you may have.

Solving the search relevance problem requires shifting the organization’s culture to emphasize cross-functional collaboration. How can the organization teach relevance engineers to understand the users’ vernacular and what they expect from search? What happens when the application is built for doctors or lawyers? Who helps the engineer understand these users’ domains? How does the organization teach a relevance engineer what makes the company the most money? Which suppliers should be kept happy?

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