Abstract: System and method for automatic entity relationship (ER) model generation for services as software is disclosed. ER model generation by automated knowledge acquisition is disclosed, and automation of knowledge generation process is disclosed. Information extraction process is automated and multilevel validation of information extraction process is provided. System comprises training module to train information extraction model, and knowledge generation module for population of ER model. Standard Operators are generated based on the ER model so generated (populated). Context aware entity extraction is implemented for the ER model generation. System and method leverages existing ER model to make the system self-learning and intelligent, and provides common platform for knowledge generation from different data sources comprising documents, database, website, web corpus, and blog.

Abstract: A system and method for creating an instance model is provided. The system provides an information extraction and modeling framework from wide spectrum of document types such as PDF, Text, HTML, LOG, CSV, images, audio/video files and DOCX. In this framework information is extracted and mapped on a domain conceptual model like ER model and the instance model is created. Initially a template model is created using the existing ER model and the plurality of data sources. The template model, the existing ER model and the information extracted from the plurality of data sources are then provided as input to generate the instance model. The system or method is not limited to extract information from log files. This can be useful for different types of files type if the structures and formats of data are different. The system can also be used with unstructured type of data sources.

Abstract: A system and method for creating an instance model is provided. The system provides an information extraction and modeling framework from wide spectrum of document types such as PDF, Text, HTML, LOG, CSV, images, audio/video files and DOCX. In this framework information is extracted and mapped on a domain conceptual model like ER model and the instance model is created. Initially a template model is created using the existing ER model and the plurality of data sources. The template model, the existing ER model and the information extracted from the plurality of data sources are then provided as input to generate the instance model. The system or method is not limited to extract information from log files. This can be useful for different types of files type if the structures and formats of data are different. The system can also be used with unstructured type of data sources.

Abstract: System and method for automatic entity relationship (ER) model generation for services as software is disclosed. ER model generation by automated knowledge acquisition is disclosed, and automation of knowledge generation process is disclosed. Information extraction process is automated and multilevel validation of information extraction process is provided. System comprises training module to train information extraction model, and knowledge generation module for population of ER model. Standard Operators are generated based on the ER model so generated (populated). Context aware entity extraction is implemented for the ER model generation. System and method leverages existing ER model to make the system self-learning and intelligent, and provides common platform for knowledge generation from different data sources comprising documents, database, website, web corpus, and blog.