Google Inc.

Lyft, Inc.

Barak Michener

Scott Meyer

John Giannandrea

Albert Yuen

Jutta Degener

Thomas Michael Dedeco

Systems and methods are disclosed for improved mapping data validation using randomness measures. Methods may include receiving a map dataset that includes a plurality of map features. A knowledge graph may be generated based on the map dataset that may include nodes representing or corresponding to the map features. Nodes corresponding to map features of a particular feature type may be identified and edges connected to the identified nodes may be processed to identify a plurality of paths. A randomness measure for the particular feature type may be determined based on the plurality of paths. The randomness measure may indicate a predictability of occurrences of map features of the particular feature type in the map dataset. The randomness measure may then be compared to a second randomness measure determined based on another map dataset.

Map data validation using knowledge graphs and randomness measures

A new database design is implemented in which everything in the database is modeled with primitives, including the links and nodes for a graph tuple store. A query syntax provides a nested tree of constraints with a single global schema. Various optimization techniques for queries and replication techniques are also described.

Database replication

Growing community of inventors

Berkeley, CA, United States of America

Barak Michener