Abstract: Systems and methods are disclosed for identifying and/or compensating for relationships between influencers and outcomes. First, a metadata model of information that characterizes relationships between influencers and outcomes is built. A query is accepted from a user, and an outcome of interest is determined based on the query. The model is subsequently relied on to flag influencers that might have an impact on an outcome of interest. The impact of these influencers on the outcome of interest is then analyzed with respect to specific conditions. When the impact is sufficiently large, the user is notified or an adjustment is made to the user's query.

Abstract: The present invention is directed to a method and mechanism to selectively evaluate data items and search queries for privacy violations. According to an embodiment of the invention, attributes of a data item are identified and quantified to evaluate its potential to violate privacy interests. Search queries can be evaluated before accessing the records according to an embodiment, which improves operating efficiency and provides additional privacy protections. The query evaluation determines whether to disallow a query or withhold a query result if an individual or a small group of individuals can be identified by the results or if variables revealed will violate privacy policies. Also, the invention enables a provider of information to systematically evaluated the selectivity and visibility of attributes that are analyzed to allow or disallow queries and to set thresholds for different combinations of attributes.