Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium that create lane graph geometries from lane graph topologies. One of the methods includes receiving data representing a topological lane path through a plurality of cells of a drivable region. From the topological lane path, an initial polyline that traverses the same plurality of cells as the topological lane path can be generated. The initial polyline can be defined by vertices located on edges of a triangulated decomposition of the drivable region. A geometry optimization process can be performed on the initial polyline to generate a final polyline according to optimization criteria. From the final polyline, a geometric lane path representing a geometry of a drivable lane that traverses the drivable region can be generated.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium that create lane graph topologies. One of the methods includes receiving data representing a drivable region of space that includes road obstacles. The representation of the drivable region can include data representing cells that represent interconnected drivable regions between the road obstacles. Each cell can contain edges, and each edge can represent that a drivable region exists between two cells. A request to generate a predicted lane graph topology for the drivable region can be received. A plurality of lane graph topologies can be enumerated, and each lane graph topology can include paths through the drivable region. A score can be computed for each lane graph topology. In response to the request, and based on the computed scores, at least one particular enumerated lane graph topology can be provided.

Abstract: A social networking system generates a newsfeed for a user to view when accessing the social networking system. Candidate stories associated with users of the social networking system are selected and an expected value score for each candidate story is determined. An expected value score is based on the probability of a user performing various types of interactions with a candidate story and a numerical value for each type of interaction. The numerical value for a type of interaction represents a value to the social networking system of the type of interaction. Based on the expected value scores, the candidate stories are ranked and the ranking used to select candidate stories for the newsfeed.

Abstract: A social networking system generates a newsfeed for a user to view when accessing the social networking system. Candidate stories associated with users of the social networking system are selected and an expected value score for each candidate story is determined. An expected value score is based on the probability of a user performing various types of interactions with a candidate story and a numerical value for each type of interaction. The numerical value for a type of interaction represents a value to the social networking system of the type of interaction. Based on the expected value scores, the candidate stories are ranked and the ranking used to select candidate stories for the newsfeed.

Abstract: A social networking system generates a newsfeed for a user to view when accessing the social networking system. Candidate stories associated with users of the social networking system are selected and an expected value score for each candidate story is determined. An expected value score is based on the probability of a user performing various types of interactions with a candidate story and a numerical value for each type of interaction. The numerical value for a type of interaction represents a value to the social networking system of the type of interaction. Based on the expected value scores, the candidate stories are ranked and the ranking used to select candidate stories for the newsfeed.

Abstract: A social networking system generates a newsfeed for a user to view when accessing the social networking system. Candidate stories associated with users of the social networking system are selected and attributes of each story are determined. The candidate stories are ranked so that the ranking of a candidate story having one or more common attributes with another candidate story is modified. This reduces the likelihood of the newsfeed presenting candidate stories with common attributes proximate to each other.

Abstract: A social networking system generates a newsfeed for a user to view when accessing the social networking system. Candidate stories associated with users of the social networking selection are selected for inclusion in the newsfeed. Based on data associated with users associated with candidate stories, the social networking system determines a neediness value for the users associated with the candidate stories. The neediness value of a user indicates a degree of assistance by the social networking system to distribute content associated with the user. For users indicated as “needy users” based on their neediness values, the social networking system modifies the location of candidate stories associated with needy users in a ranking of the candidate stories.

Abstract: A social networking system generates a newsfeed for a user to view when accessing the social networking system. Candidate stories associated with users of the social networking system are selected and attributes of each story are determined. The candidate stories are ranked so that the ranking of a candidate story having one or more common attributes with another candidate story is modified. This reduces the likelihood of the newsfeed presenting candidate stories with common attributes proximate to each other.

Abstract: A social networking system generates a newsfeed for a user to view when accessing the social networking system. Candidate stories associated with users of the social networking system are selected and an expected value score for each candidate story is determined. An expected value score is based on the probability of a user performing various types of interactions with a candidate story and a numerical value for each type of interaction. The numerical value for a type of interaction represents a value to the social networking system of the type of interaction. Based on the expected value scores, the candidate stories are ranked and the ranking used to select candidate stories for the newsfeed.