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: A method includes receiving a set of parameters for a given project and generating, using information from a knowledge database, a plurality of combinations of group members based at least in part on the set of parameters. The method also includes evaluating a set of metrics for each of the combinations of group members, the set of metrics comprising at least one novelty metric and at least one collective intelligence metric. The method further includes generating one or more strategy matrices for each of at least a subset of the combinations of group members using information from the knowledge database, evaluating the combinations of group members in the subset using the strategy matrices to determine respective predicted success values, and selecting a given one of the combinations of group members for the given project based at least in part on the sets of metrics and predicted success values.

Abstract: A method includes receiving a set of parameters for a given project and generating, using information from a knowledge database, a plurality of combinations of group members based at least in part on the set of parameters. The method also includes evaluating a set of metrics for each of the combinations of group members, the set of metrics comprising at least one novelty metric and at least one collective intelligence metric. The method further includes generating one or more strategy matrices for each of at least a subset of the combinations of group members using information from the knowledge database, evaluating the combinations of group members in the subset using the strategy matrices to determine respective predicted success values, and selecting a given one of the combinations of group members for the given project based at least in part on the sets of metrics and predicted success values.

Abstract: Assignment scheduling for service projects, in one aspect, may comprise preparing input parameter data for servicing a client service request; generating a schedule for servicing the client service request by executing an optimization algorithm with the input parameter data; determining whether the schedule is acceptable by the client; and repeating automatically the preparing, the generating, the transmitting and the determining until it is determined that the schedule is acceptable by the client, wherein each iteration automatically prepares different input parameter data for inputting to the optimization algorithm and generates a different schedule based on the different input parameter data.

Abstract: Assignment scheduling for service projects, in one aspect, may comprise preparing input parameter data for servicing a client service request; generating a schedule for servicing the client service request by executing an optimization algorithm with the input parameter data; determining whether the schedule is acceptable by the client; and repeating automatically the preparing, the generating, the transmitting and the determining until it is determined that the schedule is acceptable by the client, wherein each iteration automatically prepares different input parameter data for inputting to the optimization algorithm and generates a different schedule based on the different input parameter data.

Abstract: A metadata management system and method enables complex query searches by users, e.g., different users having different query needs, using the same infrastructure. For querying metadata, the metadata management system provides functionality for aggregating all the concepts (metadata items) and relationships of the metadata across one or more users in a common format; extracting concepts and storing them in a metadata store (e.g., a relational database); extracting relationships and modeling them in a standard semantic representation. The system and method further records users' different needs on relationships into user-specific configuration files. The system is configured for retrieving, in response to a user query, relevant data items by using the meta-data selectively. In one embodiment, a selection of meta-data used in the retrieving is determined according to captured context information.

Abstract: A method that comprises receiving a plurality of inputs including data a plurality of multiple business repositories, generating from the plurality of inputs a corpus graph as a statistical relational network, inferring a plurality of new relations between informational elements of the statistical relational network, and generating a plurality of summaries of the plurality of new relations. Further, each summary describes the informational elements of the statistical relational network associated with a corresponding risk-relation.

Abstract: A method for planning preparation of a plurality of dishes according to a plurality of corresponding recipes includes automatically identifying, by a processor, a plurality of candidate sub-recipes, wherein each candidate sub-recipe in the plurality of candidate sub-recipes comprises an intermediate component that is required by at least two of the plurality of corresponding recipes, and automatically selecting, by the processor, at least one candidate sub-recipe in the plurality of candidate sub-recipes for preparation, in accordance with at least one constraint on the preparation of the plurality of dishes.

Abstract: A method for analyzing a virtual discussion. The method may include identifying, with a processing device, a first concept relevant to a first subdiscussion associated with an online discussion. The method may also include identifying a second concept relevant to the first subdiscussion, and determining a relation between the first concept and the second concept.

Abstract: Software that uses machine logic to generate novel work products by combining known work product constituents to create constituent combinations, by performing the following steps: (i) maintaining a constituent data store, the constituent data store including identifying information for a plurality of constituents used to make combination products; (ii) receiving a set of combination preferences relating to a desired type of combination product; and (iii) applying a set of eliminational rules to the set of combination preferences and the plurality of constituents to define a raw set of proposed combination product(s), where each combination product of the raw set of proposed combination product(s) meets all the eliminational rules.

Abstract: A method for planning preparation of a plurality of dishes according to a plurality of corresponding recipes includes automatically identifying, by a processor, a plurality of candidate sub-recipes, wherein each candidate sub-recipe in the plurality of candidate sub-recipes comprises an intermediate component that is required by at least two of the plurality of corresponding recipes, and automatically selecting, by the processor, at least one candidate sub-recipe in the plurality of candidate sub-recipes for preparation, in accordance with at least one constraint on the preparation of the plurality of dishes.

Abstract: A method for analyzing a virtual discussion may include identifying, with a processing device, a first concept relevant to a first subdiscussion associated with an online discussion, identifying a second concept relevant to the first subdiscussion, and determining a relation between the first concept and the second concept.

Abstract: Assignment scheduling for service projects, in one aspect, may comprise preparing input parameter data for servicing a client service request; generating a schedule for servicing the client service request by executing an optimization algorithm with the input parameter data; determining whether the schedule is acceptable by the client; and repeating automatically the preparing, the generating, the transmitting and the determining until it is determined that the schedule is acceptable by the client, wherein each iteration automatically prepares different input parameter data for inputting to the optimization algorithm and generates a different schedule based on the different input parameter data.

Abstract: Assignment scheduling for service projects, in one aspect, may comprise preparing input parameter data for servicing a client service request; generating a schedule for servicing the client service request by executing an optimization algorithm with the input parameter data; determining whether the schedule is acceptable by the client; and repeating automatically the preparing, the generating, the transmitting and the determining until it is determined that the schedule is acceptable by the client, wherein each iteration automatically prepares different input parameter data for inputting to the optimization algorithm and generates a different schedule based on the different input parameter data.

Abstract: A system, method, and computer-readable medium that provides a streamed presentation to multiple clients over a network utilizing a presentation server that produces and streams audio, video, and uniquely identified auxiliary data objects (e.g., slides, 3D image models, sound bytes, web page, etc.) in separate sessions or channels over a network; a transmit queue associated with the presentation server to store uniquely identified repeatable auxiliary data objects; and a client that renders all data objects and stores the auxiliary data objects in a local memory cache so that they may be recalled according to their unique ID tags. The presentation server sends unique ID tags rather than the auxiliary data object content when repeated during the presentation. The client is responsive to unique ID tags to obtain an auxiliary data object from a local memory cache to render auxiliary content that is repeatedly presented during the presentation.

Abstract: A method for estimating a time required to complete an atomic task, where the atomic task is one of a plurality of atomic tasks that collectively forms a molecular task, includes obtaining, for each of a plurality of molecular tasks including the molecular task, data including: a known time required to complete each of the plurality of molecular tasks and a known list of constituent atomic tasks forming each of the plurality of molecular tasks, and estimating the time required to complete the atomic task based on the data.

Abstract: Estimating a time required to complete an atomic task, where the atomic task is one of a plurality of atomic tasks that collectively forms a molecular task, includes obtaining, for each of a plurality of molecular tasks including the molecular task, data including: a known time required to complete each of the plurality of molecular tasks and a known list of constituent atomic tasks forming each of the plurality of molecular tasks, and estimating the time required to complete the atomic task based on the data.

Abstract: A computer implemented method, system and/or computer program product schedules execution of work requests through work plan prioritization. One or more work packets are mapped to and assigned to each work request from a group of work requests. A complexity level is derived for and assigned to each work packet, and priority levels of various work requests are determined for each entity from a group of entities. A global priority for the group of work requests is then determined. The global priority and the complexity levels combine to create a priority function, which is used to schedule execution of the work requests.

Abstract: A computer implemented method, system and/or computer program product optimizes a service delivery system. A processor receives a first set of inputs that describes a current state of a service delivery system and a second set of inputs that describes a cost overhead for the service delivery system. The processor then optimizes the service delivery system in order to derive an optimized service delivery system.