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:
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:
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:
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:
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 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:
Example techniques and systems include generating cluster information to consolidate multiple locations. In one example, a method includes receiving, at a computing device, a plurality of location identifiers corresponding to a plurality of locations at which a mobile computing device was previously located, defining, by the computing device, a plurality of geographic regions based at least in part on the plurality of location identifiers, wherein each of the plurality of geographic regions defines a physical area in which at least one of the plurality of locations is located, selecting, by the computing device, a subset of the plurality of geographic regions based on respective distances between a current location of the mobile computing device and a respective reference point within each of the geographic regions, and outputting, by the computing device and for display, an indication of the subset of the plurality of geographic regions.
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 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 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.