So a set of search results for “mens shirts” will show checkboxes for brands, dropdown for average customer review, and fields for ideal price range. Or a set of search results for “electric engine schematics” will show checkboxes for file formats, a dropdown for product line, and dropdown menus for document type, author, language, or date range.
Those menus and checkboxes that users are using to refine their search are facets.
Faceting is just one of over a dozen features every search application requires to succeed in the digital workplace. Read our shopping list of what’s required to deploy a consumer-grade experience with enterprise-grade results.
Lucidworks Fusion, our development platform, for building AI-powered search applications, ships with faceting ready to deploy immediately.
As Fusion receives a query from a user and assembles a set of results it looks at common fields across the results and generates facets for them automatically. So a product catalog search for “women polo shirts” will include facets for all the colors of shirts and the sizes available and even price range of the different items. Powerful caching technology makes the addition of facet fast and instant to a search query result returned.
How to implement faceted navigation in your Apache Solr search applications.
Implementing pivot facets in Apache Solr for a better user experience.
Ready to create amazing search and data discovery apps? Contact us today to learn how Fusion can help you and our team put the power of AI, machine learning, and deep learning to work to dazzle your customers and empower your employees.
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