Abstract: The disclosure is directed to determining a social signature of a user of an application, e.g., a social networking application. The social signature can be a representation of social properties of a person, and can be determined based on various factors, e.g., user profile of the user and friends of the user. The social signature can be used for various applications, e.g., determining socially similarity of a user pair and determining if a user is a spammer. The social signature is determined as a vector of k buckets in which each of the k buckets indicates a count of friends of the user assigned to the corresponding bucket. A social similarity of a user pair is determined as a function of the social signatures of the user pair. A user is determined as likely to be a spammer if the social signature of the user is of a specified pattern.

Abstract: The disclosure is directed to determining a social signature of a user of an application, e.g., a social networking application. The social signature can be a representation of social properties of a person, and can be determined based on various factors, e.g., user profile of the user and friends of the user. The social signature can be used for various applications, e.g., determining socially similarity of a user pair and determining if a user is a spammer. The social signature is determined as a vector of k buckets in which each of the k buckets indicates a count of friends of the user assigned to the corresponding bucket. A social similarity of a user pair is determined as a function of the social signatures of the user pair. A user is determined as likely to be a spammer if the social signature of the user is of a specified pattern.

Abstract: A graph processing module is described for producing a processed graph in three phases. In a bundling phase, the graph processing module selects edges that are used to constitute paths to produce a bundled graph. In an ordering phase, the graph processing module orders paths within the bundled graph to produce an ordered bundled graph. In a separating phase, the graph processing module separates paths in the ordered bundled graph. Among other features, the graph processing module performs the selecting operation by minimizing a cost function; this has the effect of promoting bundling in the bundled graph while discouraging the presence of overly long edges in the bundled graph. The graph processing module can perform the ordering operation by selecting the ordering of paths passing through each edge based on a consideration of ordering constraints within a common subpath associated with the edge.

Abstract: A graph processing module is described for producing a visualization of a layered graph. The graph processing module operates by: bundling edges in the layered graph to produce respective edge bundles; ordering the edges associated with the edge bundles to reduce edge crossings; straightening the edges; and separating the edges in the edges bundles with respect to each other. The graph processing module can operate on a layered graph produced by the Sugiyama algorithm or some other technique, reducing clutter in the layered graph and thus improving a user's understanding of the layered graph.

Abstract: A graph processing module is described for producing a processed graph in three phases. In a bundling phase, the graph processing module selects edges that are used to constitute paths to produce a bundled graph. In an ordering phase, the graph processing module orders paths within the bundled graph to produce an ordered bundled graph. In a separating phase, the graph processing module separates paths in the ordered bundled graph. Among other features, the graph processing module performs the selecting operation by minimizing a cost function; this has the effect of promoting bundling in the bundled graph while discouraging the presence of overly long edges in the bundled graph. The graph processing module can perform the ordering operation by selecting the ordering of paths passing through each edge based on a consideration of ordering constraints within a common subpath associated with the edge.

Abstract: A graph processing module is described for producing a visualization of a layered graph. The graph processing module operates by: bundling edges in the layered graph to produce respective edge bundles; ordering the edges associated with the edge bundles to reduce edge crossings; straightening the edges; and separating the edges in the edges bundles with respect to each other. The graph processing module can operate on a layered graph produced by the Sugiyama algorithm or some other technique, reducing clutter in the layered graph and thus improving a user's understanding of the layered graph.