A Primer on Faceted Navigation and Guided Navigation
“The future is faceted.”—Peter Morville, president and founder, Semantic Studios
You’ve likely heard the buzz by now: faceted navigation truly changes the ground rules for KM, and for the many related applications where users need to find information, ranging from subscription content services to directories. It complements search and relevance ranking to fill a big hole in the process of making knowledge reusable. Faceted navigation brings the double whammy of helping users far more easily find what they’re looking for, while also helping content owners to far more efficiently manage content (or in reality, to make it even feasible to manage content at all.)
Below, I’ll talk about the distinct properties of faceted navigation that create those benefits, and later, explain how classic information science combined with breakthroughs in computer science bring it to life in a form called “Guided Navigation.”
What is faceted navigation? It’s a way to browse information, or to refine long lists of search results, along multiple dimensions, aka facets. These are orthogonal lenses through which to view the world. For example, I might search for an expert by facets like name, project, company, or date—and more likely, by some combination of those facets, selected in any sequence.
So how do facets work their powers? First, we need to state what I’ll call Busch’s golden law of facets, named for Joseph Busch of Taxonomy Strategies, a past president of the American Society for Information Science:
Four facets of 10 nodes each have the same discriminatory power as one taxonomy of 10,000 nodes.
That’s stunning. That means that with facets, I can describe a collection with 40 nodes (aka subject categories) that would take a taxonomy 10,000 nodes to describe. That’s for an idealized case, of course, but the gist of it holds true in the real world. The bottom line is that with facets, we can make do with orders of magnitude fewer categories than we needed in a taxonomy.
That’s because taxonomies are a type of pre-coordinate indexing, meaning that its builder anticipates the compound subjects people can browse along later, like “18th Century French History.” In contrast, faceted navigation is based on post-coordinate indexing, meaning that end-users string together their own compound subjects at search time. They do this by combining simple elements from multiple facets, in this example, (Time: 18th Century) + (Country: France) + (Topical Subject: History).
Reducing the number of categories we need by orders of magnitude leads directly to two primary benefits:
(1) Faceted navigation helps users more easily find what they’re looking for.
First, and most simply, it’s much easier for users to grok 40 nodes than 10,000, so in practice, they start browsing more. More importantly, faceted navigation offers users many different paths to each item of content—often dozens or hundreds of paths.
For example, before Barnes & Noble.com deployed Endeca, users could browse books through a taxonomy that offered roughly 250,000 paths. Today, with their “BookBrowser,” Barnes & Noble offers their customers literally billions of paths to browse for books. That difference between less than a million paths, and billions of paths, is the incremental value facets bring.
(2) Faceted navigation lets content owners streamline information management processes.
Most obviously, if you need orders of magnitude fewer categories or nodes than before, it becomes exponentially simpler to manage them. This leads to cascading benefits. It makes the work of auto-classifiers simpler, since they have fewer buckets to pick from. Also, facets operate independently of each other, which leads to a “schemaless” data model. This makes it simple to combine heterogeneous collections, because you don’t need to mesh facets into a single taxonomy, and it makes it simple to add facets incrementally over time.
Guiding Light
So what is the difference between faceted navigation and Guided Navigation? Guided Navigation is the name for Endeca’s version of faceted navigation. It’s a meeting of classic information science, breakthrough computer science and gritty, real-world software tools and business processes. Guided Navigation wraps search results in a context that shows users how to refine and explore their results, while constantly removing dead ends. With more than 200 commercial deployments now, Endeca has continually built its expertise with leaders like IBM, Barnes & Noble, and the Library of Congress back into the best practices reflected in the tools, UIs and APIs that give content owners editorial flexibility and managerial control over their sites, turning faceted navigation into a solution to a business problem.
Phew. That’s a lot of ground for a primer. To learn more about facets and Guided Navigation, I recommend the first issue of Philip C. Murray’s Barrington Report on Advanced Knowledge Organization and Retrieval.
Endeca, headquartered in Cambridge, Massachusetts, was founded in 1999 to transform the online search and navigation experience so that people can easily access the full breadth and depth of large data sets. Today, Endeca solutions for enterprise search and commerce are already helping businesses across a variety of sectors including financial services, manufacturing, retail, information providers and business-to-business with applications that address the information overload problems associated with enterprise information access and retrieval and content and catalog management.
Steve Papa is the CEO and co-founder of Endeca. Before starting Endeca, he was an early employee at the search engine company Inktomi, where he worked with unstructured data on a massive scale, and before that, at the data warehouse company Teradata, where he worked on structured data on a massive scale.