This blog is dedicated to the in-depth review, analysis and discussion of technologies related to the search and discovery of information. This blog represents my views only and does not reflect those of my employer, IBM.

Saturday, September 23, 2006

Drinking From the Fire Hose

So you issue a search and the search engine tells you that there are 24,832,271 results of which it displays the top ten on the first page. You scan the first page, maybe click through the next couple of pages. But have you ever wondered what those other 24 million results are? It’s a bit overwhelming – kind of like drinking from a fire hose. I for one think the number is meaningless and shouldn’t be displayed at all, especially since there is no practical way to skip say to result one million and one. But there are techniques that the search engine can employ that help you understand what’s behind that number. In particular is a technique called multifaceted search.

Rather than just show a single list of results and the total results
found number, multifaceted search displays a list of facets along side your results. Each facet represents a different dimension of your results and provides the number of results in that facet. For example, suppose I issue a search for “digital cameras”. The search engine would display my first page of results (as before) but also display the different facets for digital cameras such as by price, manufacture, or features as shown to the right. The facets act as a kind of guided navigation through the myriad of results that remain complete with counts to let you know what you’re getting into. As you click on a facet your search is reissued with the constraint defined by the facet. So clicking on Kodak would only show me the digital cameras manufactured by Kodak. The other facets (and their counts) are also updated based on this selection – the price counts would only reflect the prices offered by Kodak in this case.

Mike Moran, a colleague of mine from IBM, points out that multifaceted search is quite different from the typical "advanced search" where users are prompted to choose their criteria up front—they ask for a digital camera with 10x optical zoom for under $1000 and get the dreaded, "No results found." When they have specified more than two criteria, they don't even know which one to back off to get some results. With multifaceted search, they just pick their facets in the order of their importance to them. Invalid combinations are never shown.

So multifaceted search seeded by my original query gives me a window into what lies ahead in my result list. It has proven to be extremely effective in e-commerce applications to assist shoppers in the discovery of specific products. IBM’s OmniFind Discovery Edition is one such product that leverages multifaceted search for this purpose. The OmniFind Discovery Edition is designed to be deployed for online commerce, self service portals, and call center scenarios via a suite of tailored configurations and prepackaged industry solutions. Discovery Edition can easily extract facets from existing metadata stored in a relational database (e.g., product catalog) or from document content using advanced text analytics. Business rules expressed in natural language can be easily defined to determine when particular facets are revealed and in what context. The end result is a much richer search experience for your users, one the helps them find what they are looking for in less time.

P.S. I'm not sure what motivated my son to use the garden hose that way :-)


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5:54 AM


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