A Topology of Search Concepts

May 4, 2009
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Vegard Sandvold has an interesting post entitled “Help Me Design a Topology of Search Concepts” in which he visualizes assorted search approaches in a two-dimensional space, the two dimensions being the degree of information accessibility and whether the approach is algorithm-powered or user-powered.

His four quadrants:

  • Low information accessibility + algorithm-powered = simple search (e.g., keyword search)
  • Low information accessibility + user-powered = superficial search (e.g., collaborative filtering)
  • High information accessibility + algorithm-powered = ingenious search (e.g., question answering)
  • High information accessibility + user-powered = diligent search (e.g., faceted search)

I’m not sure how I feel about the quadrant names (though I like how my employer and I are champions of diligence!), but I do like this attempt to lay out different approaches to supporting information seeking, and I like his choice of axes…

Vegard Sandvold has an interesting post entitled “Help Me Design a Topology of Search Concepts” in which he visualizes assorted search approaches in a two-dimensional space, the two dimensions being the degree of information accessibility and whether the approach is algorithm-powered or user-powered.

His four quadrants:

  • Low information accessibility + algorithm-powered = simple search (e.g., keyword search)
  • Low information accessibility + user-powered = superficial search (e.g., collaborative filtering)
  • High information accessibility + algorithm-powered = ingenious search (e.g., question answering)
  • High information accessibility + user-powered = diligent search (e.g., faceted search)

I’m not sure how I feel about the quadrant names (though I like how my employer and I are champions of diligence!), but I do like this attempt to lay out different approaches to supporting information seeking, and I like his choice of axes.

More importantly, I hope this analysis helps advance our ability as technologists to match solutions to information seeking problems. Many of us have an intuitive sense of how to do so, but I rarely see principled arguments–particularly from vendors who may be reluctant to forgo any use case that could translate into revenue.

Of course, it would be nice to quantify these axes, or at least to formalize them a bit more rigorously. For example, how do we measure the amount of user input into the process–particuarly for applications that may involve human input at both indexing and query time? Or how do we measure information accessibility in a corpus that might include junk (e.g., spam)?

Still, this is a nice start as a framework, and I’d be delighted to see it evolve into a tool that helps people make technology decisions.

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