Abstract: A system and method for formulating a bid on an impression for an Internet advertising campaign using market forecast data are provided. The system and method comprise determining a bid policy using an advertiser goal type, an advertiser payment type, and a budget parameter. Historical impression data pertaining to the advertising campaign is sampled using any applicable sampling technique. The sampled data is used to derive forecast data that predicts the future state of the market. The bid policy and the forecast data are used to derive a spend curve, from which an optimal bid is formulated that results in a proper and efficient allocation of the advertiser's budget.

Abstract: Disclosed is a method for determining the placement of ITAPs in wireless neighborhood networks. The method disclosed provides for efficient integration of multi-hop wireless networks with the Internet by placing ITAPs at strategic locations. Initially the method provides for the formulation of the ITAP placement problem under three wireless models. For each model, methods are developed to efficiently place ITAPs in the networks. The methods aim to minimize the number of required ITAPs while guaranteeing users' bandwidth requirements. Next, a fault tolerance version of the placement method is presented that provides bandwidth guarantees in the presence of failures. Finally the methods are extended to take into account variable traffic demands by developing an approximation algorithm to simultaneously optimize ITAP placement based on demands over multiple periods.

Abstract: A system and method for calculating an effective bid per impression are disclosed. The system and method may receive a price per conversion bid of an advertiser and information from at least one user. The information may comprise a user state of the user. In some embodiments, the user state may comprise a number of times that the user has previously viewed the advertisement. The user state may be input into a user behavioral model to determine predictive values of the user behavior. An effective bid per impression may then be calculated based on the predictive values of the user and the advertiser's bid per conversion.

Abstract: Techniques for detecting social influence between users in a set of users with regard to an activity are provided. Data for each user of the set of users is received that includes a time value at which the user became active with regard to the activity, and includes at least one indication of another user in the set of users associated with the user. A first estimate of social correlation in the set of users is determined based on the data. The data is modified. For instance, the data may be modified according to a shuffle test and/or an edge reversal test. A second estimate of social correlation in the set of users is determined based on the modified data. The first estimate is compared to the second estimate to determine a degree of social influence in the set of users.

Abstract: Disclosed is a method for determining the placement of ITAPs in wireless neighborhood networks. The method disclosed provides for efficient integration of multi-hop wireless networks with the Internet by placing ITAPs at strategic locations. Initially the method provides for the formulation of the ITAP placement problem under three wireless models. For each model, methods are developed to efficiently place ITAPs in the networks. The methods aim to minimize the number of required ITAPs while guaranteeing users' bandwidth requirements. Next, a fault tolerance version of the placement method is presented that provides bandwidth guarantees in the presence of failures. Finally the methods are extended to take into account variable traffic demands by developing an approximation algorithm to simultaneously optimize ITAP placement based on demands over multiple periods.

Abstract: A system and/or method that facilitates analyzing newsgroup clusters. A data reception component receives data relating to a plurality of newsgroups and relays the data to an engine that constructs a weighted graph. The weighted graph represents a subset of the newsgroups as vertices of the graph. The vertices are connected by edges, which represent cross-postings relating to the subset of newsgroups.

Abstract: A system is disclosed for a pay-per-action (PPA) advertising model. An advertiser reports actions and pays an advertising provider for each action that is reported. The payment may be based on the rate at which the actions are reported. The action rate may be updated based on each reported action, which may modify the payment for that action and may modify the payment for previous actions. A one-time premium may be charged to advertisers and a minimum action rate may be established to encourage advertisers to accurately report actions.

Abstract: Methods, systems, and apparatuses for performing a fundraising campaign are provided. A charity is determined to receive contributions from a plurality of entities. With regard to the charity, contribution constraints are received from each entity of the plurality of entities. The contribution constraints for an entity may include a contribution budget and at least one conditional contribution conditioned on a contribution amount of at least one other entity contributing to the charity. Contribution amounts are calculated for the plurality of entities based on the contribution constraints. Each entity is informed of a corresponding contribution amount of the calculated contribution amounts, so that the entities can provide their respective contribution amounts to the charity.

Abstract: A system is disclosed for a pay-per-action (PPA) advertising model. An advertiser reports actions and pays an advertising provider for each action that is reported. The payment may be based on the rate at which the actions are reported. The action rate may be updated based on each reported action, which may modify the payment for that action and may modify the payment for previous actions. A one-time premium may be charged to advertisers and a minimum action rate may be established to encourage advertisers to accurately report actions.

Abstract: According to some example embodiments, a method includes calculating learning values associated with a plurality of listings, at least one of said learning values associated with one of said listings representing a value based, at least in part, on a probability distribution of selections of said listing. The method further includes applying said learning values to ranking scores associated with said listings to provide an updated ranking, and electronically auctioning advertising inventory to purchasers associated with said listings based, at least in part, on said updated ranking.

Abstract: Techniques for detecting social influence between users in a set of users with regard to an activity are provided. Data for each user of the set of users is received that includes a time value at which the user became active with regard to the activity, and includes at least one indication of another user in the set of users associated with the user. A first estimate of social correlation in the set of users is determined based on the data. The data is modified. For instance, the data may be modified according to a shuffle test and/or an edge reversal test. A second estimate of social correlation in the set of users is determined based on the modified data. The first estimate is compared to the second estimate to determine a degree of social influence in the set of users.

Abstract: A method for optimizing quantitative return-on-investment performance in an online advertising campaign. The advertising campaign has a finite campaign period and a finite spending budget within a system that includes a bidding facility for bidding on a plurality of advertising slots. The method seeks to optimize performance of the campaign according to an objective function that includes a marginal return on investment variable, which variable is maintained throughout a series of iterations. Techniques are disclosed for capturing campaign parameters and constraints from advertisers, and mathematical techniques are used in determining a selected advertising slot upon which to bid at each iteration. A tracking system provides a history of winning bids and forecast of inventory. After bidding, the value of the marginal return on investment variable is changed based on the results of the bidding. The next bidding operations are based on the value of the marginal return on investment variable.

Abstract: Embodiments of methods, apparatuses, or systems relating to clustering identical or disjoint keyword sets for use with auctions for online advertising space.

Abstract: Embodiments of methods, apparatuses, devices and systems associated with sorting candidate values are disclosed.

Abstract: A method of determining a display specification, includes: specifying business parameters for calculating a business value for the display specification, wherein the display specification includes a plurality of display locations and corresponding display values that are associated with business entities; specifying user parameters for calculating a user value for the display specification; selecting the display specification to improve a combination of the business value and the user value; and saving one or more values for the display specification (e.g., saving values for the display specification directly or through some related characterization.).

Abstract: The present invention leverages demarcation of an agent into both a demander and a supplier to provide a polynomial-time method of approximating a supply and demand system's equilibrium value. This provides, in one instance of the present invention, a simplified means to iteratively extract the equilibrium value. By providing demarcated data, the present invention accounts for both demand and supply effects of an agent within a modeled supply and demand system. In one instance of the present invention, a market equilibrium price vector is approximated by employing a revenue value generated for an agent in a current market equilibrium price iteration as a budget value for the agent in the next iteration. This permits market equilibrium value modeling that encompasses an agent's contributions to a market both as a buyer and a seller within the same market for a given good and/or service.

Abstract: A social network is managed by applying connectivity and similarity measures to social network information to identify possible new relationships between social network users, and then automatically suggest those identified relationships to the social network users. The social network information can include user profile information and indicate existing social relationships between the users in the social network. Users can provide feedback regarding the suggestions, including indications whether the relationship was accepted, consummated, or declined. The social network information can be updated using the feedback. Similarity measures can be based on one or more of shared contacts, or common interests or activities, or content associated with social network users, or ratings within the social network of users and/or their content. Possible relationships having similarity measures that suggest the users likely to already know each other, can be omitted and not suggested.

Abstract: The subject invention relates to systems and methods that provide a truthful incentive-compatible mechanism for budget-constrained bidders in order to facilitate asymptotically maximizing revenue with multi-unit auctions in which individual bidders have private valuation per item (e.g., bids, offer prices, utility . . . ) and overall budgets. The systems and/or methods obtain bidder private bids and budget constraint, and separate this information into groups of bids and budgets. Each group is randomly reordered and utilized to determine a profit maximizing price as a function of the bids and budgets within that group. The groups of bids and budgets and the profit maximizing prices are utilized to allocate the auctioned items to respective bidders such that the allocation is based at least in part on the bids, budgets and prices. The systems and methods can be utilized to improve online auctioning.

Abstract: A computer-implemented system that facilitates establishing price(s) associated with items comprises a clustering component that clusters a collection of non-identical items into one or more sets of non-identical items. A pricing component receives one or more of active bids and stored bids and simulates an auction of at least one non-identical item within one of the one or more sets of non-identical items as if the non-identical items within the set were identical to determine price(s) associated with the at least one non-identical item. For example, the items can be at least portions of search terms received by a search engine.

Abstract: An improved system and method for optimizing online keyword auctions subject to budget and estimated query volume constraints is provided. A linear programming model of slates of advertisements may be created using estimates of the query volume for multiple time periods for use in generating a slate of advertisements that may represent a candidate set of advertisements in order of optimal revenue to an auctioneer. Upon receiving a query request, the slate generated by the linear program or a slate generated by dynamic programming may be chosen based on whether the weighted sum of prices for the slate of advertisements computed by dynamic programming may be within a factor of the weighted sum of the prices for the slate of advertisements computed by the linear program. The chosen slate of advertisements may then be served to accompany the search results of a query request to the web browser.