Abstract: Various embodiments provide systems, computer program products and computer implemented methods. In some embodiments, a system includes a method of providing a confidence-estimation-based inference, the method includes receiving a query concerning a patient from a user, accessing an electronic health record (EHR) for the patient, the EHR including a first component regarding the patient, querying the user, using a conversational interface, for a second component regarding the patient, receiving the second component regarding the patient in response to the query, calculating a first probability density function using the first component, and a second probability density function using the second component, combining the first and second probability density functions using a Gaussian mixture model, calculating at least one conditional probability table using the Gaussian mixture model and providing the confidence-estimation-based inference based on the at least one conditional probability table.

Abstract: Various embodiments provide systems, computer program products and computer implemented methods.

Abstract: Various embodiments provide systems, computer program products and computer implemented methods. In some embodiments, a system includes a method of providing a confidence-estimation-based inference, the method includes receiving a query concerning a patient from a user, accessing an electronic health record (EHR) for the patient, the EHR including a first component regarding the patient, querying the user, using a conversational interface, for a second component regarding the patient, receiving the second component regarding the patient in response to the query, calculating a first probability density function using the first component, and a second probability density function using the second component, combining the first and second probability density functions using a Gaussian mixture model, calculating at least one conditional probability table using the Gaussian mixture model and providing the confidence-estimation-based inference based on the at least one conditional probability table.

Abstract: Various embodiments provide systems, computer program products and computer implemented methods.

Abstract: This invention provides a novel method and system for instantiating a data structure comprising a contract option including a disjunctive capability, of especial utility in enabling a new way of selling commodities or services. Rather than being a right to buy a unit of a type of item at a specified price, as is known to the prior art, the present invention enables one to secure a right to buy at least one unit of one of n-types of items at a predetermined legal consideration.

Abstract: This invention provides a novel method and system for instantiating a data structure comprising a contract option including a disjunctive capability, of especial utility in enabling a new way of selling commodities or services. Rather than being a right to buy a unit of a type of item at a specified price, as is known to the prior art, the present invention enables one to secure a right to buy at least one unit of one of n-types of items at a predetermined legal consideration.

Abstract: The carbon footprint of a supply and distribution chain is modeled as a carbon dioxide (CO2) cost that can be considered alongside monetary or dollar ($) costs in supply, manufacturing, and distribution operations. Databases on products and services, supply chain policies, and targets, costs, and/or greenhouse gas (GHG) emissions are used by a GHG calculator to output carbon footprint data and/or by a supply chain optimizer to output supply chain planning and policy data. Client computers obtain carbon footprint and/or supply chain planning and policy data by querying a server with access to a database storing calculated carbon footprint data. Input data to the GHG calculator is updated based on choices made by users of the system.

Abstract: Healthcare fraud detection is accomplished by mining social relationships and analyzing their patterns based on network data structures. Social networks are constructed which depict referral patterns (from health insurance claim information) and associations (from publicly available connection data) to analyze referral patterns and detect possible fraud, abuse and unnecessary overuse. The fraud and abuse management system supports the various aspects of fraud investigation and management, including prevention, investigation, detection and settlement. Using a unique combination of data mining capabilities and graphical reporting tools, the system can identify potentially fraudulent and abusive behavior before a claim is paid or, retrospectively, analyze providers' past behaviors to flag suspicious patterns.

Abstract: A system, method, apparatus, and computer program code for conducting a buy-side auction includes defining a plurality of transformation functions available for use in the auction. An offer to sell the item requested in the auction is received from a seller, and at least one transformation function is identified, based at least in part on the offer or the seller. The selected transformation function is applied to the offer to produce a transformed offer, and a state of the auction is updated based on the transformed offer.

Abstract: An auction is conducted by receiving, from a participant, a request for an item. An auction for the item is identified and a bid for the item is received from the participant. The received bid is forwarded to an auction for the item. In some embodiments, a transformation function associated with the participant is identified and applied to the bid to produce a transformed bid. The transformation function reflects different information about participants, the items, or the auctions (e.g, participants from different industries or from different countries).

Abstract: A system, method, apparatus, and computer program code for establishing customized financing terms includes identifying a bid for an item, identifying a financing function associated with a participant, and applying the financing function to the bid to generate a transformed bid reflecting customized financing terms.

Abstract: A system, method, apparatus, and computer program code for conducting a sell-side auction process includes defining a plurality of transformation functions available for use in the auction. A bid for the item offered in the auction is received, and at least one transformation function is identified, based at least in part on the bid or the buyer. The selected transformation function is applied to the bid to produce a transformed bid, and a state of the auction is updated based on the transformed bid.

Abstract: A system, method, apparatus, and computer program code for facilitating the sale of an item in an auction involving a plurality of participants includes identifying a bid for the item, the bid made by one of the participants. A desired configuration associated with the bid is then identified. The bid is modified to reflect the desired configuration. A status of the auction is updated based on the modified bid.

Abstract: A system, method, apparatus, and computer program code for personalized dynamic pricing in an auction involving a plurality of participants is provided. A bid for an item is identified. A transformation function associated with the bid is then identified and applied to the bid to produce a transformed bid. According to one embodiment, a state of the auction is updated based on the transformed bid. Status data representing the state of the auction may then be generated and presented to one or more participants in the auction.

Abstract: A system, method, apparatus, and computer program code for conducting a two-sided auction include defining a plurality of transformation functions available for use in the auction. A bid for an item offered in the auction is received, and at least one transformation function is identified, based at least in part on the bid or the buyer or the seller. The selected transformation function is applied to the bid to produce a transformed bid, and a state of the auction is updated based on the transformed bid. An offer for an item offered in the auction is received, and at least one transformation function is identified, based at least in part on the offer or the seller. The selected transformation function is applied to the offer to produce a transformed offer, and a state of the auction is updated based on the transformed offer.

Abstract: A method for constrained material requirements planning, optimal resource allocation, and production planning provides for an optimization of a manufacturing process by designating the amounts of various manufactured products to be produced, which products include both end products as well as subassemblies to be employed in the manufacture of one or more of the end products. In order to accomplish the optimization, the method employs an objective function such as the maximization of income in a situation wherein there are limitations on the inventory of raw materials and tools to be employed in the manufacturing process. Data describing elemental steps in the manufacturing process for the production of each end product, as well as the quantity or demand for each end product which is to be supplied, are presented as a set of linear mathematical relationships in matrix form to be inserted in a computer which determines the optimum number of each end product in accordance with an LP optimization algorithm.

Abstract: A novel allocation method for generating a feasible production schedule. The method, in response to a specified requirement q, comprises the steps of determining what quantity (r) of a product can be produced with a specified quantity of supply components; allocating a required quantity of supply components for filling a thus defined partial order; and filling a remainder of the requirement (q-r) at some later time.

Abstract: The required computational effort in the areas of production planning and logistics, scheduling, distribution and resource allocation is reduced by a procedure for solving a Discrete Activity Resource Allocation (DARA) problem. The procedure begins by reducing all activities and resources which do not contribute to maximizing benefit. Thus, all infeasible and non-profitable activities are discarded and all non-constraining resources are discarded, thereby considerably simplifying the solution to the problem. Next, an automatic mathematical model formulation of the DARA problem is performed. Based on this model, a list of cliques and covers are generated. The linear relaxation of the DARA problem using standard linear programming software is solved, and the generated list of clique and cover induced inequalities is scanned to select a set violated by the solution of the linear relaxation of the DARA problem.