Abstract: A recommendation ranking system that computes trust for entities based on negative expressions of trust. Negative expressions of trust are used to reduce the trust of entities. However, the system may discount entities that in the aggregate are distrusted. The system may be used with a social network to provide accurate, personalized recommendations for members of the social network. The network may be modeled as a voting network, with each member of the social network represented as a node and expressions of trust between members represented as weights on edges between nodes. Values of trust may be computed for nodes in the network and used to generate a recommendation. Opinions expressed on a topic may be weighted by trust in the node expressing the opinion. The system may be applied in other settings that can be modeled as a voting network, including ranking of Internet search results.

Abstract: A technique for identifying overlapping clusters of items in a data set. The technique may be used in connection with a social network or other on-line environment in which users express approval for other users, such as through votes, tags or other inputs. These expressions of approval may be used to form clusters such that entities assigned to a cluster have a higher metric of approval from other entities within the cluster than from outside the cluster. Such clusters may be arrived at through a computationally efficient approach that involves randomly selecting one or more entities as a seed for a cluster. The cluster may be grown by testing other entities, similar to those already in the cluster, to determine whether they are more preferred by those already in the cluster than those outside the cluster. Once a cluster is grown to a desired size, it may be pruned.

Abstract: A SPAM detection system is provided. The system includes a graph clustering component to analyze web data. A link analysis component can be associated with the graph clustering component to facilitate SPAM detection in accordance with the web data.

Abstract: A technique for identifying overlapping clusters of items in a data set. The technique may be used in connection with a social network or other on-line environment in which users express approval for other users, such as through votes, tags or other inputs. These expressions of approval may be used to form clusters such that entities assigned to a cluster have a higher metric of approval from other entities within the cluster than from outside the cluster. Such clusters may be arrived at through a computationally efficient approach that involves randomly selecting one or more entities as a seed for a cluster. The to cluster may be grown by testing other entities, similar to those already in the cluster, to determine whether they are more preferred by those already in the cluster than those outside the cluster. Once a cluster is grown to a desired size, it may be pruned.

Abstract: A recommendation ranking system that computes trust for entities based on negative expressions of trust. Negative expressions of trust are used to reduce the trust of entities. However, the system may discount entities that in the aggregate are distrusted. The system may be used with a social network to provide accurate, personalized recommendations for members of the social network. The network may be modeled as a voting network, with each member of the social network represented as a node and expressions of trust between members represented as weights on edges between nodes. Values of trust may be computed for nodes in the network and used to generate a recommendation. Opinions expressed on a topic may be weighted by trust in the node expressing the opinion. The system may be applied in other settings that can be modeled as a voting network, including ranking of Internet search results.

Abstract: A SPAM detection system is provided. The system includes a graph clustering component to analyze web data. A link analysis component can be associated with the graph clustering component to facilitate SPAM detection in accordance with the web data.

Abstract: Networks may be analyzed using Steiner trees. In an example embodiment, a method includes acts of receiving, accepting, creating, and analyzing. Data specifying a network is received. Steiner tree parameters are accepted. A Steiner tree model is created on the data specifying the network responsive to the Steiner tree parameters. The Steiner tree model includes a local representation having a depth constraint for neighborhood vertices. The data specifying the network is analyzed to ascertain a Steiner tree solution based on the Steiner tree model, which includes the local representation, and using a locally-oriented combinatorial algorithm.

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: Methods and systems of testing software and modeling user actions are described. In some embodiments, multiple different algorithms are provided for operating on a software model. The software model describes behavior associated with software that is to be tested. Different sets of algorithms can be selected for operating on the software model to produce a sequence of test actions that are to be used to test the software. The algorithms can be mixed and matched to achieve a desired testing result. In some embodiments, the different algorithms comprise deterministic algorithms, random algorithms, and various types of algorithms therebetween. In one embodiment, the software model comprises a state graph having nodes that represent state, and links between the nodes that represent actions. The different algorithms that are available for selection can have different graph traversal characteristics such that the state graph can be traversed in different manners.

Abstract: Networks may be analyzed using Steiner trees. In an example embodiment, a method includes acts of receiving, accepting, creating, and analyzing. Data specifying a network is received. Steiner tree parameters are accepted. A Steiner tree model is created on the data specifying the network responsive to the Steiner tree parameters. The Steiner tree model includes a local representation having a depth constraint for neighborhood vertices. The data specifying the network is analyzed to ascertain a Steiner tree solution based on the Steiner tree model, which includes the local representation, and using a locally-oriented combinatorial algorithm.

Abstract: Methods and systems of testing software and modeling user actions are described. In some embodiments, multiple different algorithms are provided for operating on a software model. The software model describes behavior associated with software that is to be tested. Different sets of algorithms can be selected for operating on the software model to produce a sequence of test actions that are to be used to test the software. The algorithms can be mixed and matched to achieve a desired testing result. In some embodiments, the different algorithms comprise deterministic algorithms, random algorithms, and various types of algorithms therebetween. In one embodiment, the software model comprises a state graph having nodes that represent state, and links between the nodes that represent actions. The different algorithms that are available for selection can have different graph traversal characteristics such that the state graph can be traversed in different manners.

Abstract: A SPAM detection system is provided. The system includes a graph clustering component to analyze web data. A link analysis component can be associated with the graph clustering component to facilitate SPAM detection in accordance with the web data.

Abstract: A SPAM detection system is provided. The system includes a graph clustering component to analyze web data. A link analysis component can be associated with the graph clustering component to facilitate SPAM detection in accordance with the web data.

Abstract: A SPAM detection system is provided. The system includes a graph clustering component to analyze web data. A link analysis component can be associated with the graph clustering component to facilitate SPAM detection in accordance with the web data.

Abstract: Dynamically auctioned advertisements are placed in networked platforms based on and associated with a specific user of the platform. The user can then select an advertisement to be associated with them during operation of the platform. Additionally, micro-endorsements or small payments can be made to the user based on their performance within the platform and their selected advertisement. The dynamic advertisement auctions can utilize impressions, selections, and successes to determine how much to charge the advertisers. Payments of the micro-endorsements can emanate from the advertiser charges. As players become more successful, increased micro-endorsements can occur. Additional payments can also be made for user loyalty to a particular advertiser. Demographics of the user can also be employed to determine which advertisements are more likely to appeal to the user and/or are more closely matched to an advertiser's target.

Abstract: Methods and systems of testing software and modeling user actions are described. In some embodiments, multiple different algorithms are provided for operating on a software model. The software model describes behavior associated with software that is to be tested. Different sets of algorithms can be selected for operating on the software model to produce a sequence of test actions that are to be used to test the software. The algorithms can be mixed and matched to achieve a desired testing result. In some embodiments, the different algorithms comprise deterministic algorithms, random algorithms, and various types of algorithms therebetween. In one embodiment, the software model comprises a state graph having nodes that represent state, and links between the nodes that represent actions. The different algorithms that are available for selection can have different graph traversal characteristics such that the state graph can be traversed in different manners.

Abstract: A computer network has links for carrying data among computers, including one or more client computers. Packet loss rates are determined for the client computers. Probability distributions for the loss rates of each of the client computers are then developed using various mathematical techniques. Based on an analysis of these probability distributions, a determination is made regarding which of the links are excessively lossy.

Abstract: Methods and systems of testing software and modeling user actions are described. In some embodiments, multiple different algorithms are provided for operating on a software model. The software model describes behavior associated with software that is to be tested. Different sets of algorithms can be selected for operating on the software model to produce a sequence of test actions that are to be used to test the software. The algorithms can be mixed and matched to achieve a desired testing result. In some embodiments, the different algorithms comprise deterministic algorithms, random algorithms, and various types of algorithms therebetween. In one embodiment, the software model comprises a state graph having nodes that represent state, and links between the nodes that represent actions. The different algorithms that are available for selection can have different graph traversal characteristics such that the state graph can be traversed in different manners.