SYSTEM AND METHOD EMPLOYING INDIVIDUAL USER CONTENT-BASED DATA AND USER COLLABORATIVE FEEDBACK DATA TO EVALUATE THE CONTENT OF AN INFORMATION ENTITY IN A LARGE INFORMATION COMMUNICATION NETWORK

An information entity rating system includes a content subsystem having a structured data sub-subsystem and an unstructured data sub-subsystem. The content subsystem receives content-based profile data for an information entity and separately processes structured and unstructured data to combine content-based profile data for an individual system user with the content-based profile data for the information entity to determine computed rating functions indicating structured and unstructured content-based value of the information entity to the user. A collaboration subsystem receives collaborative input data for the information entity and for processes the collaborative input data to determine at least one computed collaborative rating function indicating a collaboration-based value of the information entity to the user. A correlation subsystem receives data from the content subsystem and from the collaboration subsystem to determine exceptions to the computed rating functions on the basis of comparisons of data included in the content-based and collaboration data and to generate an exception data value function indicating an opposing value to at least one of the content-based and collaboration values. An output system combines the structured content-based. unstructured content-based, and collaboration-based value functions, and the exception data value function in generating an output rating predictor of the informon for consideration by the user.