Abstract: A computer-implemented method for providing a framework to identify questions and answers dynamically from a dataset based on previous learning and an evaluation score of a user. The method includes creating a library of potential questions and answers from the dataset based on the previous learning and evaluation score of the user, and generating a set of personalized questions, for the user, related to the dataset by utilizing sentence-based machine translation (SBMT) and natural language processing (NLP) tools. The method further includes identifying a plurality of answers for the set of personalized questions for the user, based on collective information available in the dataset, and providing, to the user, the plurality of answers for the set of personalized questions for verification and evaluation.

Abstract: A computer-implemented method for providing a framework to identify questions and answers dynamically from a dataset based on previous learning and an evaluation score of a user. The method includes creating a library of potential questions and answers from the dataset based on the previous learning and evaluation score of the user, and generating a set of personalized questions, for the user, related to the dataset by utilizing sentence-based machine translation (SBMT) and natural language processing (NLP) tools. The method further includes identifying a plurality of answers for the set of personalized questions for the user, based on collective information available in the dataset, and providing, to the user, the plurality of answers for the set of personalized questions for verification and evaluation.

Abstract: Generating a work-flow diagram from technology specific literature includes using an analysis of technology specific literature which includes using natural language processing (NLP), to derive semantics for a plurality of components defined in the technology specific literature. The plurality of components are associated to symbols in a component symbol database. The associated symbols are assigned to each of the plurality of components, respectively. A relationship is determined for each of the plurality of components. Nodes are assigned, and vectors are assigned when applicable, for each of the symbols. A work-flow diagram is generated for the technology specific literature using the assigned associated symbols for each of the plurality of components and the nodes and the vectors for each of the symbols.

Abstract: Generating a work-flow diagram from technology specific literature includes using an analysis of technology specific literature which includes using natural language processing (NLP), to derive semantics for a plurality of components defined in the technology specific literature. The plurality of components are associated to symbols in a component symbol database. The associated symbols are assigned to each of the plurality of components, respectively. A relationship is determined for each of the plurality of components. Nodes are assigned, and vectors are assigned when applicable, for each of the symbols. A work-flow diagram is generated for the technology specific literature using the assigned associated symbols for each of the plurality of components and the nodes and the vectors for each of the symbols.

Abstract: The educational adaptive provider architecture described herein provides a way for an educational services framework to be built on varying underlying existing technologies without any changes in the object model and services. The provider framework supports the ability to have multiple types of providers for various services, such as, for example, for authorization, authentication, communication, grouping, scoring, social-networking, storage and user functions. The educational adaptive provider architecture provides easy integration of existing institutional and educational service deployments.