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 method for extracting an implied value of a component associated with a plurality of product packages is disclosed. One embodiment of the method includes receiving data associated with a plurality of product packages. It is noted that the data comprises product package price data associated with the plurality of product packages. The data is processed utilizing a mathematical optimization to produce first output data. The first output data is processed with a statistical regression to produce second output data. The second output data includes an estimated value and its standard error of a component associated with the plurality of product packages.
Abstract:
The present invention provides an automated estimation and optimization solution for selecting the optimal bid for an item in an auction. The characteristics of the auction are selected (e.g., auction format, reserve price). A relevant bidding model, based on the characteristics of the auction, is selected. The structure of the auction is estimated based on the relevant bidding model. A bid function is determined based on the auction structure and user inputs regarding the item being bid on and the characteristics of the rival bidders. An optimal bid is determined based on the bid function and user-defined evaluation criterion. An embodiment of the present invention provides a method and system that determines the latent elements of the auction environment taking into account the strategic and information conditions with minimal assumptions on the distributions of unobserved random elements. The present invention allows a bidder to estimate the unobservable private signals of rival bidders and to determine the optimal bid the bidder can employ to optimize their evaluation criterion.
Abstract:
A method and system for selecting feedback rules for an online auction. An exemplary method may comprise controlling feedback by customizing feedback rules for an online auction substantially no earlier than entry of auction rules into an auction program by an end-user, storing the customized feedback rules for future use by the auction program, and conducting the online auction by the auction program using the feedback rules.
Abstract:
A computer-implemented method for automatic contract monitoring. An electronic version of a contract comprising at least one term and at least one penalty is received. Information relevant to enforcement of contract is monitored. A transaction related to the contract is received. Using the information, it is automatically determined whether the transaction is compliant with the contract.
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 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:
A system and method comprises simulating a multiple lot auction using a sequencing rule until bidding on all lots is closed, simulating the multiple lot auction using a different sequencing rule until bidding on all lots is closed, and comparing results of the simulated auctions with both sequencing rules.
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.