Patent ID: 8099429
Filing Date: 2012-01-17
Classification: G06F

Abstract:
1. A computer implemented system comprising the following computer executable components: an association component that relates resources based on an aggregate of user notions that are assigned to relationships, the association component incorporating an artificial intelligence component in conjunction with a training model to determine tagging trends via an automatic classifier system, a classifier in the automatic classifier system comprising a function that maps an input attribute vector x=(x1, x2, x3, x4, xn) to a confidence that an input belongs to a class comprising the function f(x)=confidence(class); a storage medium that stores the relationships; unique references that tie the resources together, the unique references comprising a plurality of links, the plurality of links appearing to users of the resources to be directly added to the resources, wherein at least one of the plurality of links is utilized to link two existing web pages based on user preferences, wherein the user preferences are independent of association preferences set by creators of the web pages; an inference component that infers relationships between the resources upon the resources being tagged as being relevant for a particular purpose, wherein the relationships are inferred by scoring at least one potential tagging trend from a list of potential tagging trends for auto suggestion to the users of the resources, wherein the scoring comprises assigning a point for each time one of the resources has been employed with a tagging trend, wherein the list of potential tagging trends is selected by employing a statistical analysis, the statistical analysis comprising a number of standard deviations away from a statistical mean, wherein resources more than two standard deviations away are employed for auto suggesting a tagging trend based on a collective user behavior; a client component that performs tagging via metadata derived from the relationships, wherein the client component further: a middle tier that implements logic involved to relate the resources and infer states of the computer implemented system, an environment and a user from a set of observations captured via events and data, wherein an inference is employed to generate a probability distribution over the states to update previously inferred schema and tighten criteria on an inferring algorithm based upon a kind of data being processed.