Abstract: Web application generation using conventional predefined template and data model approach is a technical limitation for varying user requirements. Embodiments herein provide a method and system for automated generation of web applications based on wireframe metadata generated from user requirements for a web application received in unstructured data format. The user requirements comprising a description document, and at least one of actor, requirements, use case number, use case name, and data to be collected is parsed to generate the wireframe metadata using NLP and wireframe generation rules. The wireframe metadata provides data structure of webpage details of webpages of the web application comprising a page name, a menu name, field details, a field component type, an action to be performed and an additional information. From the wireframe metadata data models are created dynamically using data modelling rules in accordance with user requirements along with task lists to generate web application.

Abstract: A system and method for inferential mining comprising a learning module to receive a predetermined dataset for generating at least one inference report and clean the received dataset using a cleaning dictionary and anthology dictionary to generate a cleansed data, a priority mapping module to associate a priority with each of the cleansed data, a classifying module to classify each of the cleansed data in a plurality of buckets, a grouping module to group each of the plurality of buckets to generate all combinations of each of the cleansed data in each of the plurality of buckets, a comparing module to compare the generated all possible combinations of each of the cleansed data to a clustering dictionary to identify insights associated with the cleansed data and a report generation module configured to generate an inference report for identified insights by matching the identified insights to a solution dictionary.

Abstract: A system and method for inferential mining comprising a learning module to receive a predetermined dataset for generating at least one inference report and clean the received dataset using a cleaning dictionary and anthology dictionary to generate a cleansed data, a priority mapping module to associate a priority with each of the cleansed data, a classifying module to classify each of the cleansed data in a plurality of buckets, a grouping module to group each of the plurality of buckets to generate all combinations of each of the cleansed data in each of the plurality of buckets, a comparing module to compare the generated all possible combinations of each of the cleansed data to a clustering dictionary to identify insights associated with the cleansed data and a report generation module configured to generate an inference report for identified insights by matching the identified insights to a solution dictionary.