Relationship Science LLC

Scott Penberthy

Neal Goldman

John C Dingee

Robert Liander

A system gathers information on important and influential people and builds a social graph. The social graph can be processed to determine a likelihood that two persons know each other. The system takes into consideration a variety of factors when determining the likelihood two persons know each other. For example, it is more likely that two people who work at a small company know each other better than two people at a big company.

Determining the likelihood persons in a social graph know each other

A system gathers information on important and influential people and builds a social graph. The social graph can be processed to determine the influence of a node in the graph or a subsection of the graph. For the influence in a subsection of the graph, only nodes with a specific type of relationship or concept is included in the influence calculation. For example, for the concept art, only relationship that have to do with art are included in the influence calculation (e.g., museum, artists, musician). In an implementation, the edge-weight of edges of the system change according to time.

Weighting paths in a social graph based on time

A system gathers information on important and influential people and builds a social graph. The social graph can be processed to determine the influence of a node in the graph or a subsection of the graph. For the influence in a subsection of the graph, only nodes with a specific type of relationship or concept is included in the influence calculation. For example, for the concept art, only relationship that have to do with art are included in the influence calculation (e.g., museum, artists, musician). In an implementation, the edge-weight of edges of the system are dependent on a property of the edge. For example, the edge-weight for an edge tracking donations is stronger if the amount of money donated is higher.

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Scott Penberthy