Rule identification from Web pages by the XRML approach

We have conducted an experiment to evaluate the potential benefit of the XRML approach with real world Web pages of Amazon.com, BarnesandNoble.com, and Powells.com. We found that 100.0% of the rules and 99.7% of the rule components could be identified and automatically generated if we do not count the statements for linkages, which generically do not exist on the Web pages. Since the linkage components occupy 11.2% of all components in the rule base, the overall limitation of automatic rule generation is 88.8%. In this setting, 88.5% of the overall rule components could be generated from the identified rules from the Web pages. The result provides solid proof that XRML can facilitate the extraction and maintenance of rules from Web pages while building expert systems in the Semantic Web environment.