Faceted search augments lexical search with afaceted navigation system, allowing users to narrow results by applying filters based on afaceted classification of the items.[1] It is aparametric search technique.[2] A faceted classification system classifies each information element along multiple explicit dimensions, facets, enabling the classifications to be accessed and ordered in multiple ways rather than in a single, predetermined,taxonomic order.[1]
Facets correspond to properties of the information elements. They are often derived by analysis of the text of an item usingentity 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.
Faceted search interfaces were first developed in the academic world byBen Shneiderman, Steven Pollitt,Marti Hearst, andGary Marchionini in the 1990s and 2000s.[3][4][5][6]The most well-known of these efforts was the Flamenco research project atUniversity of California, Berkeley, which was led by Marti Hearst.[7] Concurrently, there was development of commercial faceted search systems, notablyEndeca andSpotfire.
Within the academic community, faceted search has attracted interest primarily amonglibrary and information science researchers, and to some extent amongcomputer science researchers specializing ininformation retrieval.[8]
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, in part due to published studies that evaluated user search experience on popular sites.[9] Faceted search improves navigation and conversion by helping users find relevant products more quickly.[1]
As of 2014[update], 40% of the 50 largest US-based online retailers had implemented faceted search.[10] Examples include the filtering options that appear in the left column onamazon.com orGoogle Shopping after a keyword search has been performed.
In 1933, the noted librarianRanganathan proposed afaceted classification system for library materials, known ascolon classification. In the pre-computer era, he did not succeed in replacing the pre-coordinatedDewey Decimal Classification system.[11]
Modern online library catalogs, also known asonline public access catalogs (OPAC), have increasingly adopted faceted search interfaces. Noted examples include theNorth Carolina State University library catalog (part of the Triangle Research Libraries Network) and theOCLC OpenWorldCat system. TheCiteSeerX project[12] at thePennsylvania State University allows faceted search for academic documents and continues to expand into other facets such as table search.
In our first study on ease of search experience for users, we concluded that '27% of task failures were a result of not being able to locate a suitable item on the site, even though all of our tasks were designed so there was always at least one item available.'