Abstract: This disclosure relates generally to data processing, and more particularly to a method and system for generating ground truth labels for ambiguous domain specific tasks. The system generates reference data corresponding to a regulation statement being processed, using a crowd sourcing mechanism and then processes the reference data using an Expectation Maximization (EM) model. The EM model determines consensus with respect to ambiguity of terms/phrases, validity of questions, and validity of answers, and then based on the determined consensus, provides questions and answers to disambiguate the regulation statement.

Abstract: This disclosure relates generally to data processing, and more particularly to a method and system for generating ground truth labels for ambiguous domain specific tasks. The system generates reference data corresponding to a regulation statement being processed, using a crowd sourcing mechanism and then processes the reference data using an Expectation Maximization (EM) model. The EM model determines consensus with respect to ambiguity of terms/phrases, validity of questions, and validity of answers, and then based on the determined consensus, provides questions and answers to disambiguate the regulation statement.

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: Methods and systems described herein implement a recommendation system for providing recommendations for generating a requirements specification for agile software development. In one implementation, the system includes a processor and a memory coupled to the processor. The memory comprises a mapping module and an agile recommendation module. The mapping module is configured to map knowledge elements of at least one ontology instance selected from among a plurality of ontology instances with another ontology instance selected from among the plurality of the ontology instances. The agile recommendation module is configured to generate a knowledge corpus based on the mapped knowledge elements of the ontology instances and at least one environmental parameter, receive modifications in the knowledge corpus, and provide recommendations to generate a requirements specification based at least, in part, on the received modifications.

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.

Abstract: Methods and systems described herein implement a recommendation system for providing recommendations for generating a requirements specification for agile software development. In one implementation, the system includes a processor and a memory coupled to the processor. The memory comprises a mapping module and an agile recommendation module. The mapping module is configured to map knowledge elements of at least one ontology instance selected from among a plurality of ontology instances with another ontology instance selected from among the plurality of the ontology instances. The agile recommendation module is configured to generate a knowledge corpus based on the mapped knowledge elements of the ontology instances and at least one environmental parameter, receive modifications in the knowledge corpus, and provide recommendations to generate a requirements specification based at least, in part, on the received modifications.