Faceted search, also called faceted navigation or faceted browsing, is a technique for accessing information organized according to a faceted classification system, allowing users to explore a collection of information by applying multiple filters. A faceted classification system classifies each information element along multiple explicit dimensions, called facets, enabling the classifications to be accessed and ordered in multiple ways rather than in a single, pre-determined, taxonomic order.
Facets correspond to properties of the information elements. They are often derived by analysis of the text of an item using entity extraction techniques or from pre-existing fields in a database such as author, descriptor, language, and format. Thus, existing web-pages, product descriptions or online collections of articles can be augmented with navigational facets.
Within the academic community, faceted search has attracted interest primarily among library and information science researchers, and to some extent among computer science researchers specializing in information retrieval.
The web search world, since its very beginning, has offered two paradigms:
- Navigational search uses a hierarchy structure (taxonomy) to enable users to browse the information space by iteratively narrowing the scope of their quest in a predetermined order, as exemplified by Yahoo! Directory, DMOZ, etc.
- Direct search allows users to simply write their queries as a bag of words in a text box. This approach has been made enormously popular by Web search engines.
Over the last few years, the direct search paradigm has gained dominance and the navigational approach became less and less popular. Recently, a new approach has emerged, combining both paradigms, namely the faceted search approach. Faceted search enables users to navigate a multi-dimensional information space by combining text search with a progressive narrowing of choices in each dimension. It has become the prevailing user interaction mechanism in e-commerce sites and is being extended to deal with semi-structured data, continuous dimensions, and folksonomies.
Faceted search or navigation, in almost all applications, needs the very critical functionality of relevance adjustment. This requires that all facet values, offered as user choices, represent relevant, available possibilities. This guarantees that every choice will be successful, making the progressive narrowing process of adding facet values an information revealing and useful experience. Without that feature, searching or navigating using facet values, results in a large number of nothing found frustrating experiences.
The first product, using a search and navigation feature, which included relevance adjustment, was a document search feature called File Clerk in a Macintosh word processor called Nisus Compact first released in 1992 by Nisus Software Inc.
Subsequently around 1999 SpeedTrack Inc. was founded to focus on this innovative technology. SpeedTrack's technology is called "Technology for Information Engineering" or TIE and its GUI is called "Guided Information Access" or GIA. SpeedTrack has built a complete data analytics, mining, and search platform using, as its foundation, the initial ideas in File Clerk, but generalizing facets to be any data elements and abandoning any need of a facet hierarchy. SpeedTrack continues to evolve its technology, enabling support of all kinds of structured and unstructured data.
Mass market use
Faceted search has become a popular technique in commercial search applications, particularly for online retailers and libraries. An increasing number of enterprise search vendors provide software for implementing faceted search applications.
Online retail catalogs pioneered the earliest applications of faceted search, reflecting both the faceted nature of product data (most products have a type, brand, price, etc.) and the ready availability of the data in retailers' existing information-systems. In the early 2000s retailers started using faceted search. A 2014 benchmark of 50 of the largest US based online retailers reveals that despite the benefits of faceted search, only 40% of the sites have implemented it.  Examples include the filtering options that appear in the left column on amazon.com or Google Shopping after a keyword search has been performed.
Libraries and information science
In 1933, the noted librarian Ranganathan proposed a faceted classification system for library materials, known as colon classification. In the pre-computer era, he did not succeed in replacing the pre-coordinated Dewey Decimal Classification system.
Modern online library catalogs, also known as OPACs, have increasingly adopted faceted search interfaces. Noted examples include the North Carolina State University library catalog (part of the Triangle Research Libraries Network) and the OCLC Open WorldCat system. The CiteSeerX project at the Pennsylvania State University allows faceted search for academic documents and continues to expand into other facets such as table search.
- Enterprise Search
- Exploratory search
- Faceted classification
- Human–computer information retrieval
- Information Extraction
- Faceted Search, Morgan & Claypool, 2009
- SIGIR'2006 Workshop on Faceted Search - Call for Participation
- Smashing Magazine: The Current State of E-Commerce Search Retrieved on 2014-08-27.
- Major classification systems : the Dewey Centennial
- CiteSeerX. Citeseerx.ist.psu.edu. Retrieved on 2013-07-21.