Integrated collaborative/content-based filter structure employing selectively shared, content-based profile data to evaluate information entities in a massive information network

Abstract

An information processing system employs an integrated collaborative/content-based information filter structure to find network informons relevant to information desired by an individual user. The filter structure includes a three-level content-based filter which preprocesses informons in a first level to pass only relevant informons, applies community filters in a second level to pass relevant informons to matching communities of users, and applies in a bottom level user filters within each community to pass relevant informons to matching users. Collaborative filtering is integrated with content-based filtering through agent mind melding by which content profile data used in the content-based filtering is formed from a merger of an individual-user or member client data profile and any similar data profiles of other users or other member clients. A threshold level of similarity is required an other-user data profile to be classified as similar for merger with the individual-user data profile.