Patent application number | Description | Published |
20110295763 | MULTI-ATTRIBUTE SYSTEM FOR PROJECT PLANNING - A method of planning a project includes receiving project requirements for a project to be planned and assigning scores to the project requirements based on user preferences associated with the attributes of the requirements. The method further includes generating a numerical model of the project based on the scored requirements and optimizing the score of the numerical model to generate a matching solution that matches the project requirements to vendor offerings. | 12-01-2011 |
20120002241 | SYSTEM AND METHOD FOR ACQUIRING DOCUMENT SERVICES - A system and method for acquiring document services is disclosed. | 01-05-2012 |
20120158462 | TARGET LEVEL SETTING - Systems, methods, and machine readable and executable instructions are provided for target level setting. Target level setting may include receiving a plurality of objectives for an organization that includes a central unit and a plurality of regional units, transmitting a respective regional target level for each of the plurality of objectives assigned to each of the plurality of regional units, prompting the central unit for an approval of an increase to a first regional target level for a first of the plurality of regional units and a decrease to a second regional target level for a second of the plurality of regional units, increasing the first regional target level for the first of the plurality of regional units, and decreasing the second regional target level for the second of the plurality of regional units. | 06-21-2012 |
20120226640 | Behavior and information model to yield more accurate probability of successful outcome - A report indicating a user-reported probability of a successful outcome is received. A behavior and information model is estimated based on the report. The behavior and information model includes a behavior model component having a bias parameter and a consistency parameter. The behavior and information model includes an information model component having a first user-believed probability of a successful outcome and a second user-believed probability of a successful outcome. The behavior and information model is used to yield a model-determined probability of a successful outcome that more accurately reflects a probability of a successful outcome than the user-reported probability of a successful outcome does. | 09-06-2012 |
20130226691 | MULTI-CHANNEL CAMPAIGN PLANNING - A computer system for multi-channel campaign planning includes a digital processor, and computer readable instructions to plan and manage a multi-channel campaign. The instructions are embedded on a non-transitory, tangible memory device and executable by the processor. The instructions include a scenario outcome predicting module to predict an outcome for a scenario having a set of parameters defined for each channel of a phase of a plurality of iterative phases of the multi-channel campaign. The instructions include an adaptive learning module to generate an optimized learning component of the multi-channel campaign. The instructions include a decision optimization module to optimize the multi-channel campaign over the plurality of iterative phases. The instructions include a campaign execution module to execute the multi-channel campaign and collect outcome data. An initial phase of the plurality of phases is executed without prior outcome data for the scenario of the initial phase. | 08-29-2013 |
20130290109 | Eliciting A Customer's Product Preference Propensities Among Sub-Groups In A Social Network - A method to elicit a customer's product preference propensities among sub-groups, with each of the sub-groups having multiple members based on at least one common attribute, begins when customer action data is collected through the actions of the customer in the sub-group. The actions include the customer's propensities to purchase a product while within the sub-group and the customers' responses to displayed marketing messages or surveys while within the sub-group. The customer action data collected in the sub-group is analyzed to determine a customer's product preference propensities in the sub-group. The customer is targeted, when within the sub-group, with an electronic display that includes at least one product that corresponds to the customer's product preference propensities within the sub-group. | 10-31-2013 |
20130346033 | TREE-BASED REGRESSION - Parent node data is split into first and second child nodes based on a first partition variable to create a tree-based model. A first regression model for the first child node data relates the response variable and the predictor variable. | 12-26-2013 |
20140019210 | DETERMINING PRODUCT PRICE - Methods, systems, and computer-readable and executable instructions are provided for determining a product price. Determining a product price can include determining an initial market attraction value, a market price sensitivity, and cost information for a product. Determining a product price can also include receiving a market constraint with respect to the product and pricing the product based on the initial market attraction value, the market price sensitivity, the cost information, and the market constraint. | 01-16-2014 |
20140114727 | METHOD AND SYSTEM FOR HIERARCHICAL FORECASTING - There is provided a computer-implemented method of generating a data forecasts for different levels of an entity. The method includes generating an aggregate forecast for an upper level entity comprised of two or more components. The method also includes determining mean values and a coefficient of variation for a probability distribution corresponding to future expected decomposition rates for each of the two or more components. A probability distribution parameter vector is computed based on the mean values and the coefficient of variation. The expected future decomposition rates for each of the two or more components may be computed based on the probability distribution parameter vector and a sample observation corresponding to previously observed decomposition values of each of the two or more components. Component forecasts corresponding to each of the two or more components may be computed based on the aggregate forecast and the expected future decomposition rates. | 04-24-2014 |
20140122173 | ESTIMATING SEMI-PARAMETRIC PRODUCT DEMAND MODELS - Methods, systems, and computer-readable and executable instructions are provided for estimating semi-parametric product demand models. Estimating a semi-parametric product demand model can include identifying a set of products from input market sales data, analyzing the market sales data to determine a relationship between a plurality of factors of the set of products, and estimating the semi-parametric product demand model based on the determined relationship using iterative estimation of a plurality of incremental data trees. | 05-01-2014 |
20140188567 | PRODUCT DETERMINATION FOR A PORTFOLIO - A system includes an intersection engine to determine intersection points between multiple first functions, each first function corresponding to a product from a plurality of products and each first function based on the corresponding product's utility and profit at a given price point. The system further includes a first ranking engine to rank the intersection points and a second ranking engine to rank the first functions based on the intersection points. The system further includes a solving engine to solve a second function based on a subset of the ranked functions to determine a subset of the products to include in a product portfolio and a price for each product in the portfolio to maximize profit for the plurality of products. | 07-03-2014 |