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The feasibility of automatic recognition of recommendations is supported by empirical results. First, Usenet messages are a significant source of recommendations of Web resources: 23% of Usenet messages mention Web resources, and 30% of these mentions are recommendations. Second, recommendation instances can be machine-recognized with nearly 90% accuracy. Third, some resources are recommended by more than one person. These multiconfirmed recommendations appear to be significant resources for the relevant community. Finally, the number of distinct recommenders of a resource is a plausible measure of resource quality. A comparison of recommended resources with resources in FAQs (lists of Frequently Asked Questions maintained by human topic experts) indicates the more distinct recommenders a resource has, the more likely it is to appear in the FAQs.

PHOAKS is distinguished from …