Rather, that information
will have to be encoded into the artificial language of the Semantic Web??”another
time-consuming, tedious, and error-prone process. Pre-standard Semantic Web creation
and editing tools are already emerging to assist early adopters with Semantic
Web publishing, but even as the tools and technologies stabilize, many businesses
will be slow to follow. Furthermore, a great deal of textual data in the pre-Semantic
Web contains valuable business information, floating there along with the out-dated
debris. However, the new Web vessels??”automated agents??”cannot navigate this
old-style information. If the rising sea of human-readable knowledge on the Web
is to be tapped, and streams of it purified for computer consumption, e-business
systems must be developed to process this information, package it, and distribute
it to decision makers in time for competitive action. Tools that can automatically
extract and semantically tag business information from natural language texts will
thus comprise an important component of both the e-business systems of tomorrow,
and the Semantic Web of the day after.
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