Abstract: An inventory management system may be used to facilitate the purchase of a product by a user where the user is associated with a market segment. The system may include an inventory database and a rules database. The product may be a travel product and the purchase terms for the product may reflect a discount, an upgrade or other differentiated attribute.

Abstract: The disclosed embodiments provide a system that facilitates a purchase of a travel product. Upon detecting a participation of a user in a first qualification event associated with a first market segment, the system associates the user with the first market segment. Next, the system provides the user with a first discount offer on a first travel product associated with the first market segment. Upon obtaining an acceptance of the first discount offer from the user, the system uses the first discount offer to process a purchase of the first travel product by the user.

Abstract: The disclosed embodiments provide a system that facilitates a purchase of a travel itinerary. During operation, the system obtains a query containing one or more destination preferences provided by a user for the travel itinerary, wherein the one or more destination preferences include at least one of a region and an experience. Next, the system matches the one or more destination preferences to a set of destinations and generates a ranking of the destinations based on a set of criteria associated with the query. The system then uses the set of destinations to perform a search of available travel itineraries matching the query. Finally, the system provides the available travel itineraries to the user based on the ranking.

Abstract: The disclosed embodiments provide a system that processes a query from a user. During operation, the system obtains a set of travel products matching the query. Next, the system provides a minimum bid for each of the travel products and enables additional bidding on the travel products by a set of suppliers associated with the travel products. The system then generates a ranking of the travel products based on the minimum bid, the additional bidding, and a set of quality scores associated with the travel products. Finally, the system provides the travel products to the user based on the ranking.

Abstract: The disclosed embodiments provide a system that facilitates an opaque purchase that obscures one or more details of a travel product. Upon receiving a commitment to make the opaque purchase of the travel product by a user, the system presents the user with a set of purchase options associated with the opaque purchase, wherein the set of purchase options includes a first purchase option that conforms to one or more terms of the opaque purchase. Next, the system obtains, from the user, a selection of a purchase option from the set of purchase options. Finally, the system processes the opaque purchase with the selection.

Abstract: The disclosed embodiments provide a system that facilitates a purchase of a travel product. Upon receiving a commitment to purchase the travel product from a first supplier by a buyer, the system presents the buyer with a first upgrade option of a first premium travel product from a second supplier. If the buyer accepts the first upgrade option, the system processes the purchase with the first premium travel product. If the buyer declines the first upgrade option, the system processes the purchase with the travel product.

Abstract: The disclosed embodiments provide a system that facilitates a purchase of a travel product. Upon receiving a commitment to purchase the travel product from a first supplier by a buyer, the system presents the buyer with a first upgrade option of a first premium travel product from a second supplier. If the buyer accepts the first upgrade option, the system processes the purchase with the first premium travel product. If the buyer declines the first upgrade option, the system processes the purchase with the travel product.

Abstract: A method for maximizing revenue generated from a plurality of service level agreements (SLAs) that includes receiving a first subset of the plurality of SLAs for executing a first plurality of jobs, wherein each SLA in the first subset specifies a first maximum requested delay that is greater than an initial minimum offered delay, and wherein a price of each SLA in the first subset is defined by the maximum requested delay and a price/delay function, calculating a first expected revenue from executing the first subset, and optimizing a second subset of the plurality of SLAs by replacing the initial minimum offered delay on the initial price/delay function with a new minimum offered delay based on the expected revenue, wherein each SLA in the second subset specifies a second maximum requested delay that is greater than the new minimum offered delay.

Abstract: A method of generating an aggregated forecasting landscape for a particular advertiser's bidded term constructs standardized forecasting landscapes for each marketplace, rescales, by the advertiser's clickability in the respective marketplace, each of the standardized landscapes corresponding to the previous appearance of the advertiser's ad in that marketplace and whose appearance was attributed to the bidded term, and adds together the rescaled landscapes, thereby giving the advertiser a more accurate representation of how many total clicks he can expect for his advertisement as a function of how much he is willing/able to pay. In particular, estimation variance is reduced by introducing rank into the construction of the standardized landscapes, which increases the accuracy of the calculations.

Abstract: A method of generating an aggregated forecasting landscape for a particular advertiser's bidded term constructs standardized forecasting landscapes for each marketplace, rescales, by the advertiser's clickability in the respective marketplace, each of the standardized landscapes corresponding to the previous appearance of the advertiser's ad in that marketplace and whose appearance was attributed to the bidded term, and adds together the rescaled landscapes, thereby giving the advertiser a more accurate representation of how many total clicks he can expect for his advertisement as a function of how much he is willing/able to pay. In particular, estimation variance is reduced by introducing rank into the construction of the standardized landscapes, which increases the accuracy of the calculations.

Abstract: Apparatuses, methods, and systems directed to the estimation and modeling of market reserve prices for bidded terms in online keyword auctions with advanced match. Some embodiments of the invention estimate advertiser value distributions and advertiser bid distributions for the bidded terms and derive expected overall revenue. An optimization technique may be used to find the optimal market reserve prices for the bidded terms that maximize the expected overall revenue. In some other embodiments, a query is received for which a market reserve price is determined and exact and advanced matched advertisements are reordered for output and display.

Abstract: One embodiment of the present invention provides a system that characterizes computer system workloads. During operation, the system collects metrics for a number of workloads of interest as the workloads of interest execute on a computer system. Next, the system uses the collected metrics to build a statistical regression model, wherein the statistical regression model uses a performance indicator as a response, and uses the metrics as predictors. The system then defines a distance metric between workloads, wherein the distance between two workloads is a function of the differences between metric values for the two workloads. Furthermore, these differences are weighted by corresponding coefficients for the metric values in the statistical regression model.

Abstract: One embodiment of the present invention provides a system that computes a distance metric between computer system workloads. During operation, the system receives a dataset containing metrics that have been collected for a number of workloads of interest. Next, the system uses splines to define bases for a regression model which uses a performance indicator y as a response and uses the metrics (represented by a vector x) as predictors. The system then fits the regression model to the dataset using a penalized least squares (PLS) criterion to obtain functions f1, . . . , fP, which are smooth univariate functions of individual metrics that add up to the regression function f, such that y=f(x)+?= ? i = 1 P ? f i ? ( x i ) + ? , wherein ? represents noise. Finally, the system uses the fitted regression function to define the distance metric.

Abstract: One embodiment of the present invention provides a system that models customer behavior in a multi-choice service environment. The system constructs a probability density function f to represent probabilities of service-level choices made by customers, wherein the probability density function is a function of functional variables u?(d) and p(d); u?(d) is a utility function for a specific customer type indexed by vector ?; p(d) is a given price curve which specifies a relationship between service levels offered by a service provider and corresponding prices for the offered service levels; and u?(d) and p(d) are both functions of the offered service levels d. The system then obtains a distribution function ?(?) which specifies a probability distribution of different customer types ?. Next, the system obtains a service level-choice distribution for a population of customers as a function of a given price curve based on the probability density function f and ?(?).

Abstract: A method for maximizing revenue generated from a plurality of service level agreements (SLAs) that includes receiving a first subset of the plurality of SLAs for executing a first plurality of jobs, wherein each SLA in the first subset specifies a first maximum requested delay that is greater than an initial minimum offered delay, and wherein a price of each SLA in the first subset is defined by the maximum requested delay and a price/delay function, calculating a first expected revenue from executing the first subset, and optimizing a second subset of the plurality of SLAs by replacing the initial minimum offered delay on the initial price/delay function with a new minimum offered delay based on the expected revenue, wherein each SLA in the second subset specifies a second maximum requested delay that is greater than the new minimum offered delay.

Abstract: One embodiment of the present invention provides a system that selects bases to form a regression model for cache performance. During operation, the system receives empirical data for a cache rate. The system also receives derivative constraints for the cache rate. Next, the system obtains candidate bases that satisfy the derivative constraints. For each of these candidate bases, the system: (1) computes an aggregate error E incurred using the candidate basis over the empirical data; (2) computes an instability measure I of an extrapolation fit for using the candidate basis over an extrapolation region; and then (3) computes a selection criterion F for the candidate basis, wherein F is a function of E and I. Finally, the system minimizes the selection criterion F across the candidate bases to select the basis used for the regression model.

Abstract: One embodiment of the present invention provides a system that models computer system performance. The system empirically obtains a statistical model which comprises sets of statistical distributions for at least two types of memory-reference-related events associated with a workload executing on a processor in a computer system. These sets of statistical distributions include a first set of statistical distributions which characterize a distance between consecutive cache misses, and a second set of statistical distributions which characterize a distance between a cache miss and the beginning of a processor stall caused by the cache miss. The system then uses the statistical model to simulate the performance of the computer system executing the workload.

Abstract: A method for generating an uncertainty characterization for a system simulation model, including obtaining system simulation input, wherein the system simulation input comprises a cache simulation output, generating one of the group consisting of a deterministic uncertainty model and a stochastic uncertainty model, using the cache simulation output and the system simulation model for at least one system input configuration, and generating the uncertainty characterization for the system simulation model using one of the group consisting of the deterministic uncertainty model and the stochastic uncertainty model.

Abstract: A method for a cache architecture simulation includes obtaining a first sample set for the cache architecture using a non-stationary Gaussian field model, performing a cache architecture simulation using the first sample set to produce a first set of simulation data, and fitting a first multivariate model to the first set of simulation data.

Abstract: A method for modeling a system configuration, including isotonizing an unconstrained additive model of a cache architecture to obtain an isotonic additive model for the cache architecture, wherein the isotonic additive model is of the same functional form as the unconstrained additive model, smoothing the isotonic additive model using a flat spot technique to obtain a characterization of the cache architecture, and modeling a system configuration using the characterization of the cache architecture.