Patent ID: 7685087

Claim:
A computer-implemented method for forming a decision tree for use with an inference engine in a ubiquitous environment having a plurality of sensors, the method comprising: a) generating a data table for a set of events based on information collected by at least one of the sensors; b) establishing a weight value for each event in the set, and calculating an entropy based on the established weight value, wherein the entropy is a measure for classifying the information collected by the sensor into respective classes; and c) forming the decision tree for the collected information based on the calculated entropy; wherein the weight value in b) indicates importance of the event in the set; wherein the decision tree infers a low level data context inputted from the sensors as a high level context to be entered into a knowledge system using the inference engine; and wherein the entropy in b) is obtained by the following equation: Gain_ratio (A)=Gain (A)/split_info (A) where Gain_ratio(A) is the entropy; Gain(A) is a gain value of an attribute A, wherein the attribute A is a distinguisher for distinguishing the information collected by the at least one sensor; and split_info(A) is a partitioning information value of the attribute A.