Patent ID: 7353215

Claim:
A method for analyzing a dataset in data space to extract knowledge by identifying patterns in the dataset for classification of data within the dataset, wherein the dataset has an actual structure, the method comprising: inputting structured training data into a memory of a computer comprising a processor having software stored therein for executing a kernel machine; defining a kernel for execution by the kernel machine by: representing the training dataset in the memory as a collection of components and an actual location of each component within the training data structure, wherein the actual location is specified as indices within an index set, each of the indices corresponding to a point of reference to the actual location; applying a vicinity function to the collection of components to define subsets of components centered at different actual locations within the training dataset structure; and measuring a similarity of the subsets of components at the different actual locations to define a locational kernel corresponding to each actual location; combining the locational kernels for all of the different actual locations by performing an operation to produce a kernel on a set of structures; applying the kernel on a set of structures to the dataset in the memory to identify patterns within the datase; and storing data associated with the patterns within the dataset on a media.