Experimentation with an information filtering system that combines cognitive and sociological filtering integrated with user stereotypes

Abstract A dual-method model and system for filtering and ranking relevance of information is presented. One method is cognitive filtering, while the other is sociological filtering, which is integrated with user stereotypes. A prototype system was developed to test the applicability of the model for filtering e-mail messages, and experiments were run to determine the effects of combining the two methods in various filtering strategies. Results reveal that although cognitive filtering alone is usually more effective than sociological filtering alone, the combination of both methods yield better results than using each method individually. Ordinarily, the best filtering strategies are achieved when the two methods are used in parallel, or when cognitive filtering is the primary method, followed by sociological filtering. We conclude that the optimal filtering strategy of combining cognitive and sociological filtering is stereotype dependent; i.e., for each user stereotype, there may be a specific combination of the cognitive and sociological filtering that yields best results.