Abstract: Examples herein involve preforming a simulation of a simulated model using precomputed results of the simulation with predetermined values for a parameter set of the simulated model. In examples herein, a test sample set is selected from a sample subsets repository, and using the test sample set, determining results of a simulation of the simulated model for the test parameters.

Abstract: Systems and methods are provided for performing a fast simulation using test parameter vectors as inputs. The method includes retrieving precomputed samples from a sample repository stored in a non-volatile memory, the precomputed samples being precomputed using a simulated model, predetermined parameter vectors, and random inputs; storing respective subsets of the precomputed samples in local memories of a plurality of respective hardware processors; storing the test parameter vectors in the local memories of the hardware processors; at each of the hardware processors, selecting a subset of the precomputed samples stored in the local memory of the hardware processor based on the test parameter vectors, computing test samples by executing the simulated model using the test parameter vectors and the random inputs; and combining the subset of the precomputed samples and the test samples to produce a simulation result.

Abstract: Systems and methods are provided for performing a fast simulation using test parameter vectors as inputs. The method includes retrieving precomputed samples from a sample repository stored in a non-volatile memory, the precomputed samples being precomputed using a simulated model, predetermined parameter vectors, and random inputs; storing respective subsets of the precomputed samples in local memories of a plurality of respective hardware processors; storing the test parameter vectors in the local memories of the hardware processors; at each of the hardware processors, selecting a subset of the precomputed samples stored in the local memory of the hardware processor based on the test parameter vectors, computing test samples by executing the simulated model using the test parameter vectors and the random inputs; and combining the subset of the precomputed samples and the test samples to produce a simulation result.

Abstract: A method performed by a processing system displays a graph of a portion of a rolling horizon time series corresponding to a realization of a realization time series adjacent to a graph of the realization time series.

Abstract: Systems, methods, and machine readable and executable instructions are provided for determining offer terms from text. A method for determining offer terms from text can include mapping keywords to a domain of a procurement event, and receiving, to a computing device, an offer text associated with the procurement event. Event-specific entities are identified, by the computing device, in the offer text. The computing device determines the domain of the procurement event from the identified event-specific entities, and using the mapped keywords corresponding to the determined domain, determines offer components from the offer text, extracts offer parameters from the offer text, and constructs the offer structure using the identified event-specific entities, derived offer components, and extracted offer parameters.

Abstract: One embodiments of the present invention is directed to a data-analysis system, implemented as one or more electronic computers that execute one or more computer programs. The data-analysis system includes a metadata-extraction component that extracts indications of data entities and relationships between data entities from data stored on one or more electronic-memory and mass-storage devices, a relationship-inference component that analyzes the data to infer additional relationships between data entities, a context-determination component that determines one or more contexts within which the data is analyzed, and a navigational analysis tool, displayed on a computer device, that provides an interface that allows for navigation between relationship-interconnected data entities within each of one or more contexts, for viewing representations of data entities and relationships, and for editing and updating the relationships.

Abstract: A method performed by a processing system displays a graph of a portion of a rolling horizon time series corresponding to a realization of a realization time series adjacent to a graph of the realization time series.

Abstract: A method performed by a processing system includes comparing contracts having different lengths using uncertainty information corresponding to a non-overlap period between the contracts and providing an output that represents a comparison between the contracts in view of the uncertainty information.

Abstract: Systems, methods, and machine readable and executable instructions are provided for determining offer terms from text. A method for determining offer terms from text can include mapping keywords to a domain of a procurement event, and receiving, to a computing device, an offer text associated with the procurement event. Event-specific entities are identified, by the computing device, in the offer text. The computing device determines the domain of the procurement event from the identified event-specific entities, and using the mapped keywords corresponding to the determined domain, determines offer components from the offer text, extracts offer parameters from the offer text, and constructs the offer structure using the identified event-specific entities, derived offer components, and extracted offer parameters.

Abstract: A source offer and offer parameters regarding the source offer are received. Specifications for one or more of a number of conversion parameters are also received. The source offer is converted to a target offer, based on the offer parameters and the conversion parameters specified. Where the source offer is an incremental offer, the target offer is a cumulative offer. Where the source offer is a cumulative offer, the target offer is an incremental offer. In an incremental offer, when a volume reaches a volume threshold, a price decreases by a corresponding price discount for the volume above the volume threshold, but the price does not decrease for the volume below the volume threshold. In a cumulative offer, when the volume reaches at the volume threshold, the price decreases by the corresponding price discount for the volume both below and above the volume threshold.

Abstract: One embodiments of the present invention is directed to a data-analysis system, implemented as one or more electronic computers that execute one or more computer programs. The data-analysis system includes a metadata-extraction component that extracts indications of data entities and relationships between data entities from data stored on one or more electronic-memory and mass-storage devices, a relationship-inference component that analyzes the data to infer additional relationships between data entities, a context-determination component that determines one or more contexts within which the data is analyzed, and a navigational analysis tool, displayed on a computer device, that provides an interface that allows for navigation between relationship-interconnected data entities within each of one or more contexts, for viewing representations of data entities and relationships, and for editing and updating the relationships.

Abstract: An exemplary embodiment of the present invention provides a method of correcting data in a database table. The method includes processing a database table to identify an incorrect data field value of a data field in the database table. The method also includes obtaining a search keyword from the database table that corresponds with the incorrect data field value. The method also includes generating a regular expression based, at least in part, on a data field type corresponding with the incorrect data field value. The method also includes searching a secondary source using the search keyword and the regular expression to identify a target data value. The method also includes replacing the incorrect value in the database table with the target data value.

Abstract: Document clustering method and system utilizing both the log-based clustering method and the content-based clustering method are disclosed. The method includes the steps of generating log-based document clusters and combining vectors from the log-based document clusters with individual document clusters for content-based clustering analysis. The log-based document clusters are generated by accessing the retrieval session log, clustering the retrieval sessions, and combining the documents opened during each of the sessions of session clusters.

Abstract: Document clustering method and system utilizing both th logbased clustering method and the content-based clustering method are disclosed. The method includes the steps of generating log-based document clusters and combining vectors from the log-based document clusters with individual document clusters for content-based clustering analysis. The log-based document clusters are generated by accessing the retrieval session log, clustering the retrieval sessions, and combining the documents opened during each of the sessions of session clusters.

Abstract: Document clustering method and system utilizing both the log-based clustering method and the content-based clustering method are disclosed. The method includes the steps of generating log-based document clusters and combining vectors from the log-based document clusters with individual document clusters for content-based clustering analysis. The log-based document clusters are generated by accessing the retrieval session log, clustering the retrieval sessions, and combining the documents opened during each of the sessions of session clusters.