Abstract: An expert decision-making method is emulated based on a history of behaviors by experts in a variety of observed situations. The history of behaviors is built up from observations of actions taken by experts in analyzing a plurality of situations. Situation data representative of a situation to be processed is received, and situation features are extracted from the situation data. Each situation feature is associated with an expert behavior method used to process the situation. A behavior method is recognized from a pattern of situation features. Recognizing a behavior method is based on feature/method separation data in multidimensional space of features into areas with each area associated with a method used by experts. Parameter values for parameters in the recognized behavior method are calculated based on the situation features. The calculation of parameter values is accomplished by recognizing parameter calculation rules and calculating the parameter values using the rules.

Abstract: Images of handwritten cursive records are extracted, and an automated search on the images of the cursive records is performed based on an ASCII query for a record. A cursive equivalent of the ASCII query is matched to the images of the cursive records, and a similarity value is generated to indicate the extent of match between features of the cursive equivalent of the ASCII query and features of each cursive record. The records are sorted based upon their similarity value determined in the matching process. This provides a candidate list of cursive record images to be manually examined by a user for the purpose of making a final determination as to whether any of the cursive records on the candidate list satisfy the query.

Abstract: Images of handwritten cursive records are extracted, and an automated search on the images of the cursive records is performed based on an ASCII query for a record. A cursive equivalent of the ASCII query is matched to the images of the cursive records, and a similarity value is generated to indicate the extent of match between features of the cursive equivalent of the ASCII query and features of each cursive record. The records are sorted based upon their similarity value determined in the matching process. This provides a candidate list of cursive record images to be manually examined by a user for the purpose of making a final determination as to whether any of the cursive records on the candidate list satisfy the query.

Abstract: Images of handwritten cursive records are extracted, and an automated search on the images of the cursive records is performed based on an ASCII query for a record. A cursive equivalent of the ASCII query is matched to the images of the cursive records, and a similarity value is generated to indicate the extent of match between features of the cursive equivalent of the ASCII query and features of each cursive record. The records are sorted based upon their similarity value determined in the matching process. This provides a candidate list of cursive record images to be manually examined by a user for the purpose of making a final determination as to whether any of the cursive records on the candidate list satisfy the query.