Abstract: Methods of training a natural language processing (NLP) model comprise storing classification data associated with a plurality of words, defining model input data associated with each of the plurality of words, evaluating a cross entropy loss function to derive a loss value, and adjusting the NLP model according to the loss value derived from the cross entropy loss function. The cross entropy loss function may be defined to include one or more special loss terms to support training of the NLP model on the basis of incomplete classification data, such as in cases where not all possible classes are considered by the annotator, where not all words are provided with annotated classes, where consensus has not been reached between annotators, and/or where not all classes have been defined.

Abstract: An authoring tool may comprise a plurality of predefined functions displayed in a visual manner. A user may select functions from the predefined functions to create a logic map. The authoring tool may read metadata from a metadata store corresponding to the functions. The authoring tool may generate an intermediate language, and compile the metadata from the intermediate language to a desired language. The authoring tool may execute the logic map on data in a data management system.

Abstract: An authoring tool may comprise a plurality of predefined functions displayed in a visual manner. A user may select functions from the predefined functions to create a logic map. The authoring tool may read metadata from a metadata store corresponding to the functions. The authoring tool may generate an intermediate language, and compile the metadata from the intermediate language to a desired language. The authoring tool may execute the logic map on data in a data management system.

Abstract: A business object model, which reflects data that is used during a given business transaction, is utilized to generate interfaces. This business object model facilitates commercial transactions by providing consistent interfaces that are suitable for use across industries, across businesses, and across different departments within a business during a business transaction. In some operations, software creates, updates, or otherwise processes information related to Currency Conversion and Date and Time business objects.

Abstract: A business object model, which reflects data that is used during a given business transaction, is utilized to generate interfaces. This business object model facilitates commercial transactions by providing consistent interfaces that are suitable for use across industries, across businesses, and across different departments within a business during a business transaction. In some operations, software creates, updates, or otherwise processes information related to Currency Conversion and Date and Time business objects.

Abstract: The present invention provides a Dynamic Relaxation and Motivational Agent (“DRMA”) capable of interacting with a user in real-time and in multi-modes (audio, video, visual, tactile, etc.). Based on user preferences (pre-configured), current request, and the mood of the user, the DRAMA is able to dynamically generate a customized relaxation experience. During the relaxation experience, the user can be motivated and can easily learn and more receptive to suggestions. The DRMA Agent functions as a guide capable of reacting to various user inputs including tactile, physical key/touch screen inputs, voice, breathing noise, silence, background noise, etc.