When working with search user experience, it’s often necessary to discover a suitable information strategy for an organization or business. An information strategy can potentially have a huge influence on how the search for information is facilitated. Are the users in question generally seeking precise answers to quick questions, or are they seeking to explore a broader selection of opportunities? Question answering will generally require a more ambitious use of technology, while exploration and discovery places greater focus on communicating with the users. Perhaps an early decision to acquire software with semantic analysis capabilities will lead the project towards greater use of technology, while users studies may reveal that users are keen on spending time researching the cheapest flights to their holiday destination. Understanding the integration of business goals, user needs, and technological possibilities is in any case vital for a successful and sustainable information strategy.
Two recent articles in Technology Review reflect some of my latest writing on 4 different approaches to search user experience. The article by Daniel Tunkelang entitled “To Search, Ask” is very much in line with what I like to call Diligent Search, while the article on Wolfram Alpha is describing something closer to Ingenious Search. I find these articles very interesting, and I believe you will think so too.
Daniel Tunkelang (CTO, Endeca), a strong believer in faceted search and set retrieval, and an advocate for HCIR, prefers search engines that are more like conversational librarians. Rather than guessing what the users need, these systems provide users with opportunities to clarify and elaborate their intent. If the engine isn’t sure what users what, it just asks them.
Stephen Wolfram, the physicist and maker of Mathematica, has recently launched the computational knowledge engine Wolfram Alpha. In response to questions, Alpha is meant to compute answers rather than list Web pages, and pushes technology to the limit in order to anticipate what the users need. It attempts to achieve this by means of a constantly expanding collection of curated data sets, an elaborate calculator, and a natural-language interface for queries.