Abstract: According to embodiments, methods, systems, and computer program products are provided for receiving one or more input compositions comprising one or more materials, assigning a material vector to each material, learning, for each of the input compositions, a composition vector based on the material vectors of the materials that form each composition, assigning predicted rating values having a confidence level to each of the composition vectors, selecting a composition to be rated based on the confidence levels, presenting the selected composition to be rated to a user, receiving a user rating for the composition to be rated; adjusting the predicted rating values and confidence levels of the composition vectors that have not been rated by the user, and generating a predictive model to predict a user's ratings for compositions when confidence levels of each composition vector is above a predetermined threshold value.

Abstract: According to embodiments, methods, systems, and computer program products are provided for receiving one or more input compositions comprising one or more materials, assigning a material vector to each material, learning, for each of the input compositions, a composition vector based on the material vectors of the materials that form each composition, assigning predicted rating values having a confidence level to each of the composition vectors, selecting a composition to be rated based on the confidence levels, presenting the selected composition to be rated to a user, receiving a user rating for the composition to be rated; adjusting the predicted rating values and confidence levels of the composition vectors that have not been rated by the user, and generating a predictive model to predict a user's ratings for compositions when confidence levels of each composition vector is above a predetermined threshold value.

Abstract: According to embodiments, methods, systems, and computer program products are provided for generating material compositions including receiving, by a processor, a plurality of material inputs that collectively form one or more known material compositions, assigning a vector space value to each of the plurality of material inputs, wherein each vector space value is unique for each material input, receiving a first constraint and a second constraint, and generating a transformed material composition based on the vector space value, the first constraint, and the second constraint.

Abstract: According to embodiments, methods, systems, and computer program products are provided for receiving one or more input compositions comprising one or more materials, assigning a material vector to each material, learning, for each of the input compositions, a composition vector based on the material vectors of the materials that form each composition, assigning predicted rating values having a confidence level to each of the composition vectors, selecting a composition to be rated based on the confidence levels, presenting the selected composition to be rated to a user, receiving a user rating for the composition to be rated; adjusting the predicted rating values and confidence levels of the composition vectors that have not been rated by the user, and generating a predictive model to predict a user's ratings for compositions when confidence levels of each composition vector is above a predetermined threshold value.

Abstract: According to embodiments, methods, systems, and computer program products are provided for generating material compositions including receiving, by a processor, a plurality of material inputs that collectively form one or more known material compositions, assigning a vector space value to each of the plurality of material inputs, wherein each vector space value is unique for each material input, receiving a first constraint and a second constraint, and generating a transformed material composition based on the vector space value, the first constraint, and the second constraint.

Abstract: According to embodiments, methods, systems, and computer program products are provided for receiving one or more input compositions comprising one or more materials, assigning a material vector to each material, learning, for each of the input compositions, a composition vector based on the material vectors of the materials that form each composition, assigning predicted rating values having a confidence level to each of the composition vectors, selecting a composition to be rated based on the confidence levels, presenting the selected composition to be rated to a user, receiving a user rating for the composition to be rated; adjusting the predicted rating values and confidence levels of the composition vectors that have not been rated by the user, and generating a predictive model to predict a user's ratings for compositions when confidence levels of each composition vector is above a predetermined threshold value.

Abstract: Enterprise learning system may receive as input learning goals for a learner. Learning goals may also be specified by job-roles. The system may output course-sequence recommendations, sequence-associations to learning goals and learning-goal recommendations. A semantic analysis may automatically relate learning-goals to learning assets and job-roles. Computational semantic relation-finding may leverage available knowledge-bases. A sequence-recommendation recommends course or learning asset sequences to the learner based on historical usage, the learner's current and/or desired job-roles and learning goals.

Abstract: An application management service account benchmarking. An account profile is generated associated with a target account. Data associated with the target account collected and prepared for benchmarking. A benchmarking pool is formed to include a set of accounts with which to compare the target account. Operational KPIs are designed for benchmarking analysis. Measurements associated with the operational KPIs are determined for the target account and the set of accounts in the benchmarking pool. Benchmarking is conducted based on the measurements. A graph of a distance map is generated and presented on a graphical user interface. Post benchmarking analysis is performed that suggests an action to be performed for the target account.

Abstract: An application management service account benchmarking. An account profile is generated associated with a target account. Data associated with the target account collected and prepared for benchmarking. A benchmarking pool is formed to include a set of accounts with which to compare the target account. Operational KPIs are designed for benchmarking analysis. Measurements associated with the operational KPIs are determined for the target account and the set of accounts in the benchmarking pool. Benchmarking is conducted based on the measurements. A graph of a distance map is generated and presented on a graphical user interface. Post benchmarking analysis is performed that suggests an action to be performed for the target account.

Abstract: A method, apparatus and program product which facilitate contract formation by making explicit the labor content of a bid presented by a second party (potential supplier) to a first party (buying the services or goods). Software executing on an information handling system and controllably accessible to both parties which provides a common set of the job roles, job skills and costs associated with a bid to be presented. Such clarification by use of a common taxonomic table enables the buying party to better understand the cost build up for the labor component and to rank the cost build up among several bidders.

Abstract: A system implementing a situation-oriented directory for retrieving a stakeholder identification includes a memory storing a relational database corresponding to the situation-oriented directory including a plurality of attribute-value combinations and a plurality of stakeholder identifications, wherein the plurality of attribute-value combinations are mapped to the plurality of stakeholder identifications such that for each attribute-value combination exactly one stakeholder is mapped, and a processor in communication with the memory for receiving a query and retrieving the stakeholder identification from among the plurality of stakeholder identifications based on the attribute-value combinations.

Abstract: A user interface service composer determines, based on a user interface request from a user interface consumer, one of a plurality of user interface service providers to be invoked; and consults a particular entry (corresponding to the service provider to be invoked) in a user interface data catalog having a plurality of entries for the plurality of user interface service providers. A request message, for rendering a user interface requested in the user interface request received from the user interface consumer, is routed from the user interface service composer to the given one of the plurality of user interface service providers that is to be invoked. The request message includes configuration parameters and interaction-related data, and is formatted in accordance with the particular entry in the user interface data catalog.

Abstract: A system implementing a situation-oriented directory for retrieving a stakeholder identification includes a memory storing a relational database corresponding to the situation-oriented directory including a plurality of attribute-value combinations and a plurality of stakeholder identifications, wherein the plurality of attribute-value combinations are mapped to the plurality of stakeholder identifications such that for each attribute-value combination exactly one stakeholder is mapped, and a processor in communication with the memory for receiving a query and retrieving the stakeholder identification from among the plurality of stakeholder identifications based on the attribute-value combinations.