Obviously, searching can get pretty complex, and many pitfalls can prevent a user from achieving success. So how does it get done in the non-Web world, and can we learn anything from it?
In the real world, reference librarians and other information professionals often make the difference. In fact, without them, civilization would creak to a grinding halt. They are better than anyone else at finding information because they break up what seems to be a huge, complex information need into simpler, more digestible components by conducting a reference interview that is designed to learn more about the information need and its context (unless, of course, you're just looking for the bathroom or the copiers!).
Before you get spooked by the term reference interview, consider that you probably have been through quite a few of them yourself. When you go to the library and ask someone behind the reference desk a question, they'll probably respond with an open question, such as "Can you tell me a little more about how you'll be using this information?" The interview will often continue with more specific questions, such as "Do you need this information for business (or school, a dissertation, personal enjoyment, etc.)?" "Do you need it right away (or can we take some time to do some more involved searching or interlibrary loan for it)?" "Are you looking for something at no cost (or would you like us to do a literature search in some commercial databases like LEXIS/NEXIS or DIALOG)?" "Are you looking for a few items (or do you need all there is)?" and so on. These interactive iterations help both the librarian understand what you're looking for, and may also help you better understand your own needs by forcing you to articulate them. In effect, both you and the librarian engage in associative learning about the information need. Associative learning comes naturally to humans, but is extremely difficult for software systems to handle.
Can a web site do what a reference librarian does? Well, sort of, but not quite. We've already covered a sample of the variation found in users and their information needs, and we know that well-architected sites can largely address these needs. If we can determine the major needs of our sites' users and take steps to address them, then perhaps we'll cover 80% of all possible search queries. That would be wonderful, as most sites probably don't do half that well. But that other 20%, the really tricky stuff, can't be handled by automated means like a web site. You really do need humans to help out in those situations, because only humans are really good at figuring out context and knowing the right questions to ask. Don't hold your breath for this issue to be solved by an automated approach, such as with an intelligent agent. Instead, consider making someone in your organization (maybe the librarian, if your organization employs one) responsible for handling the tough queries, and make sure your site actively seeks feedback and directs it to those human information specialists.
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