Abstract: Resolving ambiguities in regulatory documents is necessary to ensure organizations and people are able to be best possible compliant with regulations or standards. Current approaches attempting to automatically resolve ambiguities in regulatory documents have limitations when it comes to incorporating fairness or reduce chances of subjective interpretation. Embodiments of the present disclosure provide a method and system for automatically resolving ambiguities in regulations. To disambiguate a given regulatory sentence the method augments the regulation sentence with relevant internal information extracted using a set of predefined linguistic patterns and relevant external information extracted from external sources identified using a Neural Network (NN) model.

Abstract: Resolving ambiguities in regulatory documents is necessary to ensure organizations and people are able to be best possible compliant with regulations or standards. Current approaches attempting to automatically resolve ambiguities in regulatory documents have limitations when it comes to incorporating fairness or reduce chances of subjective interpretation. Embodiments of the present disclosure provide a method and system for automatically resolving ambiguities in regulations. To disambiguate a given regulatory sentence the method augments the regulation sentence with relevant internal information extracted using a set of predefined linguistic patterns and relevant external information extracted from external sources identified using a Neural Network (NN) model.

Abstract: The present subject matter relates to an automated classification of business rules. In one embodiment, a method for automated classification of the business rules comprises identifying a business rule from a text document, wherein the business rule comprises one or more rule intents. Further, the method comprises comparing the one or more rule intents in the business rule with rule intents associated with a plurality of rule types in a rule repository. Furthermore, the method comprises classifying the business rule under at least one of the rule types based on the comparison.

Abstract: A system(s) and method(s) for identifying project requirement are described herein. The system identifies the architecturally significant functional requirements from the functional requirements from a client/customer. The system further classifies the identified architecturally significant functional requirements into specific classes based on the architectural impact they may have on the project. Subsequently, the system generates a meta schema related to architecturally significant functional requirements based on the classification of architecturally significant functional requirements and pre-defined schema. Thereafter, system recommends the specific probing questions from the bank of probing questions to unearth unspecified or underspecified architecturally relevant information based on the generated meta schema.

Abstract: Systems and methods for automated interpretation of legal regulations are described. The described systems implement a method that includes receiving a plurality of legal regulations and deconstructing the plurality of legal regulations based on at least one of a regulatory rule model and Minsky's frames to form a computer interpretable regulation repository. The method also includes identifying rule intents applicable to each of the deconstructed plurality of legal regulations; and classifying the plurality of legal regulations into at least one rule act based at least on the identified rule intents.

Abstract: A system(s) and method(s) for identifying project requirement are described herein. The system identifies the architecturally significant functional requirements from the functional requirements from a client/customer. The system further classifies the identified architecturally significant functional requirements into specific classes based on the architectural impact they may have on the project. Subsequently, the system generates a meta schema related to architecturally significant functional requirements based on the classification of architecturally significant functional requirements and pre-defined schema. Thereafter, system recommends the specific probing questions from the bank of probing questions to unearth unspecified or underspecified architecturally relevant information based on the generated meta schema.

Abstract: Systems and methods for automated interpretation of legal regulations are described. The described systems implement a method that includes receiving a plurality of legal regulations and deconstructing the plurality of legal regulations based on at least one of a regulatory rule model and Minsky's frames to form a computer interpretable regulation repository. The method also includes identifying rule intents applicable to each of the deconstructed plurality of legal regulations; and classifying the plurality of legal regulations into at least one rule act based at least on the identified rule intents.

Abstract: The present subject matter relates to an automated classification of business rules. In one embodiment, a method for automated classification of the business rules comprises identifying a business rule from a text document, wherein the business rule comprises one or more rule intents. Further, the method comprises comparing the one or more rule intents in the business rule with rule intents associated with a plurality of rule types in a rule repository. Furthermore, the method comprises classifying the business rule under at least one of the rule types based on the comparison.