Abstract: In one implementation, a computer-implemented method includes obtaining travel information that indicates travel patterns for a mobile computing device that is associated with a user; identifying a current context for the mobile computing device and the user; identifying one or more destination locations that the user has at least a threshold likelihood of travelling to with the mobile computing device based on the current context and the obtained travel information; generating a prediction that one or more events have at least a threshold probability of occurring along one or more of a plurality of routes for travelling to the identified one or more destination locations; selecting a particular route from the plurality of routes to recommend to the user based on the current context and the prediction of the one or more events; and providing route information that identifies the selected particular route.

Abstract: A computing system is described that obtains, based at least in part on information included in at least one previous communication associated with a user of a computing device, an indication of a future location and a future time and event information associated with the future location and the future time. The computing system obtains a duration of time for the user to travel from a current location of the computing device to the future location, and, based at least in part on the duration of time, obtains a departure time at which the user is predicted to need to depart from the current location in order to arrive at the future location by an arrival time based on the event. The computing system outputs, for transmission to the computing device, an indication associated with the event and including information indicative of the departure time.

Abstract: The present invention pertains to geographical image processing of time-dependent imagery. Various assets acquired at different times are stored and processing according to acquisition date in order to generate one or more image tiles for a geographical region of interest. The different image tiles are sorted based on asset acquisition date. Multiple image tiles for the same region of interest may be available. In response to a user request for imagery as of a certain date, one or more image tiles associated with assets from prior to that date are used to generate a time-based geographical image for the user.

Abstract: In one implementation, a computer-implemented method includes obtaining travel information that indicates travel patterns for a mobile computing device that is associated with a user; identifying a current context for the mobile computing device and the user; identifying one or more destination locations that the user has at least a threshold likelihood of travelling to with the mobile computing device based on the current context and the obtained travel information; generating a prediction that one or more events have at least a threshold probability of occurring along one or more of a plurality of routes for travelling to the identified one or more destination locations; selecting a particular route from the plurality of routes to recommend to the user based on the current context and the prediction of the one or more events; and providing route information that identifies the selected particular route.

Abstract: In general, techniques, devices, and systems for filtering location information received from multiple computing devices are described. In one example, a method includes receiving a first plurality of location indicators from a first mobile computing device and a second plurality of location indicators from a second mobile computing device, wherein the first and second computing devices are both associated with a single user and the first and second pluralities of location indicators are representative of geographical locations at which each of the respective first and second mobile computing devices has been located. The method may also include determining a subset of the location indicators for a period of time, all location indicators included in the subset being associated with the one of the first or second mobile computing devices that moved with the user during the period of time, and outputting information related to the subset of the location indicators.

Abstract: The systems and techniques disclosed herein provide the ability to determine locations visited by a user and associate relevant location labels with the locations visited based on contact information. In some examples, a location label can be applied based on a match between a location visited and information stored in a user's contact list. In other examples, a user can efficiently designate a contact and location label to be associated with a location visited. In still other examples, if a location visited by a user is not listed in the user's contact list, but is otherwise known to the system, the location visited can be appropriately labeled and the corresponding contact in the user's contact list can be updated to include the location visited.

Abstract: A computing system is described that obtains, based at least in part on information included in at least one previous communication associated with a user of a computing device, an indication of a future location and a future time and event information associated with the future location and the future time. The computing system obtains a duration of time for the user to travel from a current location of the computing device to the future location, and, based at least in part on the duration of time, obtains a departure time at which the user is predicted to need to depart from the current location in order to arrive at the future location by an arrival time based on the event. The computing system outputs, for transmission to the computing device, an indication associated with the event and including information indicative of the departure time.

Abstract: Embodiments relate to determining commute routes and clustering commute routes from a user's location history. Points in the user's location history may be clustered to find the user's home and work locations. Additionally, points along the user's commute may be identified to determine the user's typical commute. Similar commutes can be clustered together, and used to suggest various services to the user.

Abstract: The systems and techniques disclosed herein provide the ability to determine locations visited by a user and associate relevant location labels with the locations visited based on contact information. In some examples, a location label can be applied based on a match between a location visited and information stored in a user's contact list. In other examples, a user can efficiently designate a contact and location label to be associated with a location visited. In still other examples, if a location visited by a user is not listed in the user's contact list, but is otherwise known to the system, the location visited can be appropriately labeled and the corresponding contact in the user's contact list can be updated to include the location visited.

Abstract: The disclosed implementations are related to hierarchical spatial data structures with 3D data versioning for generating packet data. The packet data can be used by a client application to determine the availability of data at certain levels of a hierarchical spatial data structure. A 3D index table storing data version information can be used to support data updates and to ensure that a consistent view of data is provided to clients without suffering interruptions in service.

Abstract: The present invention pertains to geographical image processing of time-dependent imagery. Various assets acquired at different times are stored and processing according to acquisition date in order to generate one or more image tiles for a geographical region of interest. The different image tiles are sorted based on asset acquisition date. Multiple image tiles for the same region of interest may be available. In response to a user request for imagery as of a certain date, one or more image tiles associated with assets from prior to that date are used to generate a time-based geographical image for the user.

Abstract: The systems and techniques disclosed herein provide the ability to determine locations visited by a user and associate relevant location labels with the locations visited based on contact information. In some examples, a location label can be applied based on a match between a location visited and information stored in a user's contact list. In other examples, a user can efficiently designate a contact and location label to be associated with a location visited. In still other examples, if a location visited by a user is not listed in the user's contact list, but is otherwise known to the system, the location visited can be appropriately labeled and the corresponding contact in the user's contact list can be updated to include the location visited.

Abstract: Techniques are disclosed herein for inferring user interests and serving recommendations to the user. An example for serving recommendations based on inferred user interests is described. The example includes receiving a plurality of location data points for a user, the location data points including a geographic position and a time, and storing the location data points in a data store. The location data points are processed using a processor in communication with the data store to generate visited place data for the user where the visited place data represents a location visited by the user, a category of the location visited, and a time. A histogram of the visited place data is built across categories of locations visited and the histogram is stored in the data store. Recommendations are then served to the user within a category represented on the histogram.

Abstract: The systems and techniques disclosed herein provide the ability to determine locations visited by a user and associate relevant location labels with the locations visited based on contact information. In some examples, a location label can be applied based on a match between a location visited and information stored in a user's contact list. In other examples, a user can efficiently designate a contact and location label to be associated with a location visited. In still other examples, if a location visited by a user is not listed in the user's contact list, but is otherwise known to the system, the location visited can be appropriately labeled and the corresponding contact in the user's contact list can be updated to include the location visited.

Abstract: A computing system is described that obtains, based at least in part on information included in at least one previous communication associated with a user of a computing device, an indication of a future location and a future time and event information associated with the future location and the future time. The computing system obtains a duration of time for the user to travel from a current location of the computing device to the future location, and, based at least in part on the duration of time, obtains a departure time at which the user is predicted to need to depart from the current location in order to arrive at the future location by an arrival time based on the event. The computing system outputs, for transmission to the computing device, an indication associated with the event and including information indicative of the departure time.

Abstract: A computing system is described that obtains, based at least in part on information included in previous communication associated with a user of a computing device, an indication of a future location and a future time and further obtains information associated with an event which is associated with the future location and the future time. The computing system obtains a duration of time for the user to travel from a current location of the computing device to the future location, and further obtains, based at least in part on the duration of time, a departure time at which the user is predicted to need to depart from the current location in order to arrive at the future location by an arrival time that is determined based at least in part on the future time. The computing system outputs, for transmission to the computing device, an indication of the departure time.

Abstract: A computing system extracts, based on one or more electronic messages sent or received by a user of a mobile computing device, travel plan information associated with the user of the mobile computing device. The travel plan information may indicate a destination to which the user is planning to travel. In response to extracting the travel plan information, the computing system may send an instruction to the mobile computing device to cache, in advance of the user arriving at the destination, information associated with the destination. In this way, the mobile computing device may access the information associated with the destination while at the destination, even if the mobile computing device is unable to access the information via a wireless communication channel.

Abstract: In one implementation, a computer-implemented method includes obtaining travel information that indicates travel patterns for a mobile computing device that is associated with a user; identifying a current context for the mobile computing device and the user; identifying one or more destination locations that the user has at least a threshold likelihood of travelling to with the mobile computing device based on the current context and the obtained travel information; generating a prediction that one or more events have at least a threshold probability of occurring along one or more of a plurality of routes for travelling to the identified one or more destination locations; selecting a particular route from the plurality of routes to recommend to the user based on the current context and the prediction of the one or more events; and providing route information that identifies the selected particular route.

Abstract: In some examples, systems and techniques can determine a respective visit likelihood for each respective destination of a plurality of destinations based at least in part on a respective distance between the respective destination and a geographic location from a location history associated with a user and a comparison between a time associated with the geographic location and a visit likelihood distribution across time. The systems and techniques can then sort at least some of the plurality of destinations. In other examples, systems and techniques can determine whether a user is likely to visit a place during a future instance of a timeslot based at least in part on a location history associated with the user. The systems and techniques can then output information relating to the place prior to the beginning of the future instance of the timeslot.

Abstract: The systems and techniques disclosed herein provide the ability to determine locations visited by a user and associate relevant location labels with the locations visited based on contact information. In some examples, a location label can be applied based on a match between a location visited and information stored in a user's contact list. In other examples, a user can efficiently designate a contact and location label to be associated with a location visited. In still other examples, if a location visited by a user is not listed in the user's contact list, but is otherwise known to the system, the location visited can be appropriately labeled and the corresponding contact in the user's contact list can be updated to include the location visited.