Abstract: Methods, systems, and computer program products for determining transit routes through crowd-sourcing, for determining an estimated time of arrival (ETA) of a vehicle of the transit route at a given location, and for providing predictive reminders to a user for catching a vehicle of the transit route. A server receives signal source information about wireless signal sources detected by user devices, including information about a first wireless signal source detected by some devices. The server determines that the first wireless signal source is moving. The server determines that the first wireless signal source is associated with a public transit route upon determining that the signal source information satisfies one or more selection criteria. The server stores information associating the first wireless signal source with the public transit route as transit movement data corresponding to the public transit route.

Abstract: Methods, systems, and computer program products for determining transit routes through crowd-sourcing, for determining an estimated time of arrival (ETA) of a vehicle of the transit route at a given location, and for providing predictive reminders to a user for catching a vehicle of the transit route. A server receives signal source information about wireless signal sources detected by user devices, including information about a first wireless signal source detected by some devices. The server determines that the first wireless signal source is moving. The server determines that the first wireless signal source is associated with a public transit route upon determining that the signal source information satisfies one or more selection criteria. The server stores information associating the first wireless signal source with the public transit route as transit movement data corresponding to the public transit route.

Abstract: Some embodiments provide a method for defining travel paths in a map region. The method identifies location data collected over a period of time from multiple mobile devices. The method aggregates the location data for each of multiple map areas. The aggregated data for each map area identifies an amount of mobile device traffic passing through the map area over the period of time. The method normalizes the aggregated data for a subset of the multiple map areas based on analysis of the relative amounts of mobile device traffic. The method uses the normalized data to identify paths in the map.

Abstract: Methods, systems, and computer program products for determining transit routes through crowd-sourcing, for determining an estimated time of arrival (ETA) of a vehicle of the transit route at a given location, and for providing predictive reminders to a user for catching a vehicle of the transit route. A server receives signal source information about wireless signal sources detected by user devices, including information about a first wireless signal source detected by some devices. The server determines that the first wireless signal source is moving. The server determines that the first wireless signal source is associated with a public transit route upon determining that the signal source information satisfies one or more selection criteria. The server stores information associating the first wireless signal source with the public transit route as transit movement data corresponding to the public transit route.

Abstract: Methods, systems, and computer program products for determining transit routes through crowd-sourcing, for determining an estimated time of arrival (ETA) of a vehicle of the transit route at a given location, and for providing predictive reminders to a user for catching a vehicle of the transit route. A server receives signal source information about wireless signal sources detected by user devices, including information about a first wireless signal source detected by some devices. The server determines that the first wireless signal source is moving. The server determines that the first wireless signal source is associated with a public transit route upon determining that the signal source information satisfies one or more selection criteria. The server stores information associating the first wireless signal source with the public transit route as transit movement data corresponding to the public transit route.

Abstract: Some embodiments provide a method for defining travel paths in a map region. The method identifies location data collected over a period of time from multiple mobile devices. The method aggregates the location data for each of multiple map areas. The aggregated data for each map area identifies an amount of mobile device traffic passing through the map area over the period of time. The method normalizes the aggregated data for a subset of the multiple map areas based on analysis of the relative amounts of mobile device traffic. The method uses the normalized data to identify paths in the map.

Abstract: Methods, systems, and computer program products for determining transit routes through crowd-sourcing, for determining an estimated time of arrival (ETA) of a vehicle of the transit route at a given location, and for providing predictive reminders to a user for catching a vehicle of the transit route. A server receives signal source information about wireless signal sources detected by user devices, including information about a first wireless signal source detected by some devices. The server determines that the first wireless signal source is moving. The server determines that the first wireless signal source is associated with a public transit route upon determining that the signal source information satisfies one or more selection criteria. The server stores information associating the first wireless signal source with the public transit route as transit movement data corresponding to the public transit route.

Abstract: Georeferenced transaction data is harvested (“crowd-sourced”) from client devices and sent to a network-based map service. The map service performs cluster analysis on location data points in the harvested data, resulting in one or more clusters representing local densities of transaction occurrences. Data vectors including supplemental data are obtained from one or more vendors. Location data points included in the data vectors are compared to center coordinates of the one or more clusters and the closest matching cluster/vector pair provides a mapping to POI data in a POI database. The mapped POI data is updated with the supplemental data. In some implementations, transaction timestamps in the harvested data are used to estimate the business hours of a business POI.

Abstract: Techniques for address point data mining are described. An address point data mining method, system, or program product can determine geographic coordinates of an address based on geographic locations of one or more user devices. Each user device can be a mobile device operable to determine a location using a global navigation system (e.g., GPS), wireless signal triangulation, or other techniques. During the course of a time period (e.g., a day or week), the user device can stay at a location for a significant amount of time. The system can crosscheck this location with a geocoded geographic coordinates of a registered address (e.g., a billing address) that is associated with the mobile device. The system can determine whether the geocoded geographic coordinates are accurate based on result of the crosscheck.

Abstract: Methods, systems, and computer program products for determining transit routes through crowd-sourcing, for determining an estimated time of arrival (ETA) of a vehicle of the transit route at a given location, and for providing predictive reminders to a user for catching a vehicle of the transit route. A server receives signal source information about wireless signal sources detected by user devices, including information about a first wireless signal source detected by some devices. The server determines that the first wireless signal source is moving. The server determines that the first wireless signal source is associated with a public transit route upon determining that the signal source information satisfies one or more selection criteria. The server stores information associating the first wireless signal source with the public transit route as transit movement data corresponding to the public transit route.

Abstract: Methods, systems, and computer program products for determining transit routes through crowd-sourcing, for determining an estimated time of arrival (ETA) of a vehicle of the transit route at a given location, and for providing predictive reminders to a user for catching a vehicle of the transit route. A server receives signal source information about wireless signal sources detected by user devices, including information about a first wireless signal source detected by some devices. The server determines that the first wireless signal source is moving. The server determines that the first wireless signal source is associated with a public transit route upon determining that the signal source information satisfies one or more selection criteria. The server stores information associating the first wireless signal source with the public transit route as transit movement data corresponding to the public transit route.

Abstract: Methods, systems, and computer program products for determining transit routes through crowd-sourcing, for determining an estimated time of arrival (ETA) of a vehicle of the transit route at a given location, and for providing predictive reminders to a user for catching a vehicle of the transit route. A server receives signal source information about wireless signal sources detected by user devices, including information about a first wireless signal source detected by some devices. The server determines that the first wireless signal source is moving. The server determines that the first wireless signal source is associated with a public transit route upon determining that the signal source information satisfies one or more selection criteria. The server stores information associating the first wireless signal source with the public transit route as transit movement data corresponding to the public transit route.

Abstract: Georeferenced transaction data is harvested (“crowd-sourced”) from client devices and sent to a network-based map service. The map service performs cluster analysis on location data points in the harvested data, resulting in one or more clusters representing local densities of transaction occurrences. Data vectors including supplemental data are obtained from one or more vendors. Location data points included in the data vectors are compared to center coordinates of the one or more clusters and the closest matching cluster/vector pair provides a mapping to POI data in a POI database. The mapped POI data is updated with the supplemental data. In some implementations, transaction timestamps in the harvested data are used to estimate the business hours of a business POI.

Abstract: Methods, systems, and computer program products for determining transit routes through crowd-sourcing, for determining an estimated time of arrival (ETA) of a vehicle of the transit route at a given location, and for providing predictive reminders to a user for catching a vehicle of the transit route. A server receives signal source information about wireless signal sources detected by user devices, including information about a first wireless signal source detected by some devices. The server determines that the first wireless signal source is moving. The server determines that the first wireless signal source is associated with a public transit route upon determining that the signal source information satisfies one or more selection criteria. The server stores information associating the first wireless signal source with the public transit route as transit movement data corresponding to the public transit route.

Abstract: Methods, systems, and computer program products for determining transit routes through crowd-sourcing, for determining an estimated time of arrival (ETA) of a vehicle of the transit route at a given location, and for providing predictive reminders to a user for catching a vehicle of the transit route. A server receives signal source information about wireless signal sources detected by user devices, including information about a first wireless signal source detected by some devices. The server determines that the first wireless signal source is moving. The server determines that the first wireless signal source is associated with a public transit route upon determining that the signal source information satisfies one or more selection criteria. The server stores information associating the first wireless signal source with the public transit route as transit movement data corresponding to the public transit route.

Abstract: Methods, systems, and computer program products for determining transit routes through crowd-sourcing, for determining an estimated time of arrival (ETA) of a vehicle of the transit route at a given location, and for providing predictive reminders to a user for catching a vehicle of the transit route. A server receives signal source information about wireless signal sources detected by user devices, including information about a first wireless signal source detected by some devices. The server determines that the first wireless signal source is moving. The server determines that the first wireless signal source is associated with a public transit route upon determining that the signal source information satisfies one or more selection criteria. The server stores information associating the first wireless signal source with the public transit route as transit movement data corresponding to the public transit route.

Abstract: Techniques for address point data mining are described. An address point data mining method, system, or program product can determine geographic coordinates of an address based on geographic locations of one or more user devices. Each user device can be a mobile device operable to determine a location using a global navigation system (e.g., GPS), wireless signal triangulation, or other techniques. During the course of a time period (e.g., a day or week), the user device can stay at a location for a significant amount of time. The system can crosscheck this location with a geocoded geographic coordinates of a registered address (e.g., a billing address) that is associated with the mobile device. The system can determine whether the geocoded geographic coordinates are accurate based on result of the crosscheck.

Abstract: Methods, computer-readable media, and computer systems for finding wireless network access points. Geographic location information describing a geographic location of a computer system within a geographic area is received. From a storage medium that stores information defining multiple geographic cells and, for each cell, information defining multiple wireless network access points, a particular geographic cell within which the geographic location described by the geographic location information is located is identified. Access points within the particular geographic cell are identified, and provided in response to receiving the geographic location information.

Abstract: Methods, computer-readable media, and computer systems for finding wireless network access points. Geographic location information describing a geographic location of a computer system within a geographic area is received. From a storage medium that stores information defining multiple geographic cells and, for each cell, information defining multiple wireless network access points, a particular geographic cell within which the geographic location described by the geographic location information is located is identified. Access points within the particular geographic cell are identified, and provided in response to receiving the geographic location information.

Abstract: It can be difficult to predict what the layout of a document will be if the document contains several content elements, some of which are associated with different positioning schemes. In one embodiment, elements are shown in different layers based on their positioning schemes. For example, a first layer includes elements that are associated with non-overlapping positioning schemes, and a second layer includes elements that are associated with overlapping positioning schemes. When the document is viewed from above, the layers “collapse” onto each other, and the document appears to have a conventional (two-dimensional) page rendering. However, when the document is viewed from an angle, the layers appear separately in three-dimensional space, similar to an exploded view. The separate layers reveal the positioning schemes of the various elements and the layout interactions between those elements. This visualization technique helps a user understand how various elements are positioned within the document.