Abstract: A computer-implemented method, computer program product and computing system for maintaining an ML object collection that defines a plurality of ML objects; and associating usage criteria with each of the plurality of ML objects.

Abstract: A computer-implemented method, computer program product and computing system for obtaining the phrase-based synonym ML object from an ML object collection that defines a plurality of ML objects; adding the phrase-based synonym ML object to a probabilistic model; generating a list of synonym phrases via the phrase-based synonym ML object; and enabling the list of synonym phrases to be edited by a user.

Abstract: A computer-implemented method, computer program product and computing system for allowing a plurality of entities to access an ML object collection that defines a plurality of ML objects; and making an inquiry to a first entity, chosen from the plurality of entities, about a specific ML object defined within the ML object collection.

Abstract: A computer-implemented method, computer program product and computing system for identifying the need for a probabilistic model to process existing content; importing a navigatable structure; utilizing the navigatable structure as a basis for an initial probabilistic model; and determining whether the initial probabilistic model is a good explanation of the existing content.

Abstract: A computer-implemented method, computer program product and computing system for obtaining the word-based synonym ML object from an ML object collection that defines a plurality of ML objects; adding the word-based synonym ML object to a probabilistic model; generating a list of synonym words via the word-based synonym ML object; and enabling the list of synonym words to be edited by a user.

Abstract: A computer-implemented method, computer program product and computing system for identifying a specific uncertainty in a probabilistic model; providing a user with one or more initial questions concerning the specific uncertainty; and receiving a response from the user concerning the one or more initial questions.

Abstract: A computer-implemented method, computer program product and computing system for accessing an ML object collection that defines a plurality of ML objects; and assigning a confidence level to a specific ML object, chosen from the plurality of ML objects, concerning the applicability of the specific ML object for use with a probabilistic model.

Abstract: A computer-implemented method, computer program product and computing system for accessing an ML object collection that defines a plurality of ML objects; and identifying a first ML object chosen from the plurality of ML objects defined within the ML object collection.

Abstract: A computer-implemented method, computer program product and computing system for maintaining an ML object collection that defines at least one ML object, wherein the at least one ML object defines a plurality of linked versions of the ML object.

Abstract: A computer-implemented method, computer program product and computing system for rendering an initial item; receiving a selection command concerning the initial item from a user; selecting a preferred response item, chosen from a plurality of response items defined for the initial item, wherein the preferred response item is associated with a path that is based, at least in part, upon one or more user criteria associated with the user; and rendering the preferred response item.

Abstract: A computer-implemented method, computer program product and computing system for rendering a result set; receiving a user input concerning a subgroup of items chosen from the result set; and processing the user input with respect to the subgroup of items to generate an output.

Abstract: A computer-implemented method, computer program product and computing system for receiving non-structured content concerning a plurality of items. The non-structured content is processed to identify one or more proposed features for the plurality of items. The one or more proposed features are provided to a user for review. Feature feedback concerning the one or more proposed features is received. The one or more proposed features are modified based, at least in part, upon the feature feedback received from the user, thus generating one or more approved features.