Abstract: Methods, apparatuses and systems directed to online auctions for keywords used in queries processed by online search engines. Particular implementations of the invention are directed to correlating a distribution of values to a distribution of bids and an optimal minimum reserve price based on historical bid data accumulated as part of producing search results.

Abstract: The present invention provides a method and apparatus for sponsored Internet-based search simulation. The present invention includes receiving a search query sequence that represents a search query and selecting one or more advertisements based on the search query sequence. The present invention further includes filtering the plurality of advertisements based on advertising budget data and determining a number of user-selections on the advertisements using a pre-calculated user-selection model. The present invention further includes updating advertiser account information regarding advertising rates in response to the number of user-selections and generating simulation log data reflecting the advertisings, user-selections and advertising account information. This technique thereby performs the simulation based on user search queries, in response to user-selection models and references the user-selection and advertisement with advertisement budget data, consistent with live sponsored search result operations.

Abstract: An embodiment of the invention is a method for proactive failover using user-defined rules. An event log of a first server node is monitored to check for user-specified application events. One of the user-specified application events corresponding to an impending failure in an application running on a first server node is detected. In automatic response to the detected impending failure, a proactive failover process is executed to transfer the application to a second server node for continued execution, the second server node being connected to the first server node in a cluster.

Abstract: The method of the present invention is useful in a computer system including at least two server nodes, each of which can execute clustered server software. The program executes a method for monitoring failure situations to reduce downtime. The method includes the step of detecting an event causing one of the failure situations, and then the method determines if the event affects one of the server nodes. If it is determined the event does affect one of the server nodes, the method then determines if the event exceeds a threshold value. If it is determined the event exceeds a threshold value, the method executes a proactive failover. If the event is not specific to a cluster node, but indicates an impending or actual failure of the cluster software, the method identifies and initiates an appropriate action to fix the condition or provide a workaround (if available) that will preempt an impending failure of the cluster system or would enable a restarting of a failed cluster software.

Abstract: A business process and computer system known as the “Target Pricing System” (TPS) that generates an optimum bid or value for a competitively bid good or service. The system is resident on one or more host processors in connection with one or more data stores, and includes a product model that defines list values for the bid using stored price data and costs the values using stored cost data, a competitor net price model that calculates an equivalent competitor net price for the value, and a market response model that calculates the probability of winning with the value as a function of price. The system further preferably includes an optimization model that computes the target price of an optimal value that maximizes expected contribution for the bid or value. The system alternately further includes a benefits model for calculating the benefits of using target pricing over a pre-existing approach, and strategic objects which each affect the target price.