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January 26, 2004 (Computerworld) -- Text-search technology is finally coming of age. Stand-alone search "solutions" can still be ludicrously bad: Monsanto's top 10 hits for "fertilizer" lead to boilerplate legal disclaimers, Boeing's top 10 hits for "jet fighter" feature discontinued aircraft, and Toyota's top 10 hits for "Camry" are in Chinese. But when text search is integrated into a broader application framework, the story is much happier. Search is a clear success in several specific niches, such as online retailing or regulation-driven document management. And as the means improve of integrating text with other kinds of data, a much broader range of text-aware applications is becoming practical as well.
Some of the more intriguing opportunities include:
Upgrading your Web presence. Surely you already have a search capability on your Web site. But it could probably be a lot better.
Upgrading your online documentation. If you provide a lot of technical information online, it's probably hard to navigate. Helping customers find what they need more easily can save both them and you a lot of money. Effective text search is crucial in this effort.
Navigating applications more easily. Large e-commerce sites are often best navigated via text queries such as "John Grisham" or "red turtleneck sweaters." The same may be true for back-office systems such as merchandising or purchasing.
Helping your people find one another. Suppose an employee looks for information on a subject and finds vaguely relevant information written by a colleague. There's a good chance that talking with this person will help your employee find out what he needs to know. Not only is such expertise-finding invaluable in global engineering and consulting organizations, but it also can be helpful in figuring out how to approach particularly tricky or important sales challenges.
Digging into text mining. You probably have a wealth of text and even voice records pertaining to customer contacts -- service call reports, call center reports, sales call reports, customer letters and e-mails, even recorded phone calls or chat sessions. Analyzing these could turn up crucial information about customer segmentation or about product strengths, weaknesses and flaws. It's a gamble, because you don't know how much you'll really find -- but just like the original form of data mining, it's a gamble worth taking.
All of these application scenarios depend on text being related to other kinds of data.

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