Patent Document ID: 7873643
Application ID: 11688053

Base Claim:
1. A computer implemented method of predicting, comprising the steps of: receiving a pre-existing classification structure; receiving an instance to be predicted, comprising at least one attribute to be predicted; determining a best host for the instance to be predicted; optionally placing the instance to be predicted into a location relative to at least one child of the best host within the pre-existing classification structure; determining a confidence level for an occurrence of an at least one possible value for the at least one attribute to be predicted; querying each member of the pre-existing classification structure to perform a prediction process on the instance, wherein the prediction process is based at least in part on a relevance factor associated with the attribute; and returning a prediction profile, comprising at least one possible value for the at least one attribute to predict and the corresponding confidence level for the at least one possible value for the at least one attribute to be predicted.

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Claim 2:
2. The computer implemented method of claim 1 , wherein determining the best host for the instance to be classified comprises: processing class concept nodes of the classification structure, comprising the steps of: receiving a class concept node of the classification structure; calculating a delta cohesiveness measurement (ΔCM) value between the instance to be classified and the class concept node; and storing the largest ΔCM value and the corresponding class concept node at each level of the classification tree; determining the largest ΔCM value over all levels of the classification structure; and storing the class concept node corresponding to the largest ΔCM value over all levels of the classification structure.