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It has been a long-standing joke among users that of the 1,000 results a search engine might produce, you're lucky if one is useful, and that could be the last file presented on the list. And if you type in a common word such as "sweater," you'll have to dig through a pile of Web sites--selling everything from winter clothing to knitting products to dog accessories--to get to the item for which you are looking.
As companies build their knowledge databases, more accurate search engines are crucial to produce the best results for the customer--whether that customer is an internal user looking for the latest marketing report or a paying client surfing the Web for a size 6 pair of jeans.
One way search engines are becoming more effective is by using natural language queries. Instead of just typing sweaters, you can type, "Where can I buy women's red sweaters?" and get more accurate results.
Search engines are also working to address an annoyance often stated by search users, particularly those in large corporations with numerous databases throughout the organization: Before they can perform a search, they have to know where the item is located.
The common response is that if they knew in which database last year's sales forecast was stored, they wouldn't need a search engine. Many search engines are addressing that problem by searching across multiple databases as well as the Web to find the appropriate documents.
"We really are stepping up the capabilities of search to reduce the frustration of the user," says Stephen Brown, VP of product strategies for Vality (vality.com, to be acquired by Ascential Software). "Search is starting to move into a next generation of product expectation and market requirements."
One key way that search engines are changing is through personalization, Brown says. The search engine begins to learn the patterns of an individual's searches and to present them with the information that most closely matches their needs.