1. A method for performing context inference in a mobile device, the method comprising: receiving, at a classifier implemented in one or more integrated circuits of the mobile device, sensor data from at least one data source associated with the mobile device, wherein the at least one data source comprises one or more sensors of the mobile device; determining, by the classifier implemented in the one or more integrated circuits, a first context class for the received sensor data, the first context class corresponding to a context state indicated by the received sensor data; determining, by the classifier implemented in the one or more integrated circuits, that a confidence value associated with the determination of the first context class is below a threshold value; creating, by the classifier implemented in the one or more integrated circuits, a fusion class for the received sensor data at least in part by fusing the first context class for the received sensor data and at least a second context class for the received sensor data, the at least the second context class being different from the first context class, wherein the fusion class semantically encompasses the first context class and the at least the second context class and further wherein the fusion class is broader than each of the first context class and the at least the second context class; substituting, by the classifier implemented in the one or more integrated circuits, the fusion class for the first context class; and outputting, by the classifier implemented in the one or more integrated circuits, the fusion class as the inferred context of the mobile device.
1. A method for performing context inference in a mobile device, the method comprising: receiving, at a classifier implemented in one or more integrated circuits of the mobile device, sensor data from at least one data source associated with the mobile device, wherein the at least one data source comprises one or more sensors of the mobile device; determining, by the classifier implemented in the one or more integrated circuits, a first context class for the received sensor data, the first context class corresponding to a context state indicated by the received sensor data; determining, by the classifier implemented in the one or more integrated circuits, that a confidence value associated with the determination of the first context class is below a threshold value; creating, by the classifier implemented in the one or more integrated circuits, a fusion class for the received sensor data at least in part by fusing the first context class for the received sensor data and at least a second context class for the received sensor data, the at least the second context class being different from the first context class, wherein the fusion class semantically encompasses the first context class and the at least the second context class and further wherein the fusion class is broader than each of the first context class and the at least the second context class; substituting, by the classifier implemented in the one or more integrated circuits, the fusion class for the first context class; and outputting, by the classifier implemented in the one or more integrated circuits, the fusion class as the inferred context of the mobile device. 10. The method of claim 1 wherein the creating the fusion class comprises selecting the fusion class from a plurality of predetermined available fusion classes.