Abstract: A method is provided to using a generative adversarial network to generate map geometry from images representing probe data. Methods may include: receiving a rasterized image representative of probe data within a geographic area, where each pixel of the rasterized image includes a property representing at least one component of the probe data; generating a prediction image of road features within the geographic area using a generative adversarial network based on trained model parameters and the rasterized image; determining one or more map elements based, at least in part, on the prediction image and georeferenced locations of the road features within the prediction image; and updating a map of the geographic area with one or more map elements.

Abstract: System and methods for augmenting search results with external/user-provided data fields not contained in a primary datastore. A method includes receiving, by a processor, a location-based query; searching, by the processor, a primary datastore for one or more candidates for the location-based query; identifying, by the processor, one or more data fields for the one or more candidates contained in a secondary datastore, the one or more data fields not contained in the primary datastore; augmenting, by the processor, the one or more candidates with the one or more data fields; and providing, by the processor, the augmented one or more candidates.

Abstract: System and methods for augmenting search results with external/user-provided data not contained in a primary datastore. On demand matching is used at run time to match entries in the primary datastore with information in a secondary datastore that is neither indexed nor pre-matched. A location-based query is received. Candidates are generated by searching a primary datastore. A machine learned entity matching network matches the candidates with information in the secondary datastore. The candidates are augmented with the information and returned as search results.

Abstract: A method, apparatus and computer program product are provided to determine a semantic privacy index that quantifies the risk associated with re-identification of a trajectory following anonymization of the trajectory. In the context of a method, information regarding a trajectory is received. After the trajectory has been map matched to a portion of a road network, the method associates contextual information comprising one or more map features with the trajectory. The method also provides the information regarding the trajectory and the contextual information comprising the one or more map features to a risk estimation model in order to generate the semantic privacy index.

Abstract: System and methods for augmenting search results with external/user-provided data fields not contained in a primary datastore. A method includes receiving, by a processor, a location-based query; searching, by the processor, a primary datastore for one or more candidates for the location-based query; identifying, by the processor, one or more data fields for the one or more candidates contained in a secondary datastore, the one or more data fields not contained in the primary datastore; augmenting, by the processor, the one or more candidates with the one or more data fields; and providing, by the processor, the augmented one or more candidates.

Abstract: An approach is provided for automatically identifying transportation transition regions (e.g., off-road pickup/drop-off locations) based on probe trajectory data. The approach involves, for example, determining a geographic area that encompasses a point of interest and an associated off-road region. The approach also involves retrieving probe trajectories that intersect the geographic area. The approach further involves segmenting the one or more probe trajectories into a plurality of segments that include on-road and/or off-road segments. The approach also involves processing the plurality of segments to identify one or more transition segments that include a transition involving an on-road segment of the one or more on-road segments or an off-road segment of the one or more off-road segments. The approach further involves clustering one or more probe points of the one or more transition segments to identify the transportation transition region.

Abstract: An apparatus for the quantification of privacy risk in geographic data for probe devices in a geographic region includes a database, a sub-trajectory module, a candidate list calculator, and a provision module. The database is configured to store trajectory data based on sequences of sensor measurements. The sub-trajectory module is configured to receive trajectory data points based on sequences of sensor measurements of the probe devices collected in the geographic region and determine sub-trajectories from changes in trajectory identifiers. The candidate list calculator is configured to concatenate at least two of the sub-trajectories based on at least one concatenation parameter. The provision module is configured to calculate a reconstruction rate in the trajectory data and provide the reconstruction rate for a quantification of privacy risk to an external device.

Abstract: A method, apparatus and computer program product are provided to determine a semantic privacy index that quantifies the risk associated with re-identification of a trajectory following anonymization of the trajectory. In the context of a method, information regarding a trajectory is received. After the trajectory has been map matched to a portion of a road network, the method associates contextual information comprising one or more map features with the trajectory. The method also provides the information regarding the trajectory and the contextual information comprising the one or more map features to a risk estimation model in order to generate the semantic privacy index.

Abstract: An apparatus for the quantification of privacy risk in geographic data for probe devices in a geographic region includes a database, a sub-trajectory module, a candidate list calculator, and a provision module. The database is configured to store trajectory data based on sequences of sensor measurements. The sub-trajectory module is configured to receive trajectory data points based on sequences of sensor measurements of the probe devices collected in the geographic region and determine sub-trajectories from changes in trajectory identifiers. The candidate list calculator is configured to concatenate at least two of the sub-trajectories based on at least one concatenation parameter. The provision module is configured to calculate a reconstruction rate in the trajectory data and provide the reconstruction rate for a quantification of privacy risk to an external device.