Systems and methods to select locations of interest based on distance from route points or route paths
Selection of offers, locations or merchants based on their distances from a portion of a user's route and their affinity for the user is disclosed. A route employed by a user for travelling to a destination is obtained and segmented at identified vertices. Locations that are proximate to the route segments are determined. The proximate locations are further analyzed to obtain their specific distances from a selected portion such as the user's origin or destination or any route segment. Location based services are associated with those proximate locations that are closest to the selected portion on the user's route or those with the better utility.
1. A method implemented in a computing apparatus, the method comprising:
identifying, by the computing apparatus, a route of a user device having a plurality of segments defined by a set of locations on the route;
for each respective point of a plurality of points on the route, computing, by the computing apparatus, a respective threshold distance from a predetermined function of:
a length of one of the plurality of segments on which the respective point is located; and
a predetermined distance;
selecting, by the computing apparatus, a point of interest for the route of the user device based at least in part on a determination that at least one of the points on the route has a threshold distance that is longer than a distance between the point of interest and the one of the points on the route;
transmitting, by the computing apparatus, information related to the point of interest to the user device while the user device is on the route; and
computing a utility value of the point of interest based on an affinity value of the user device for the point of interest and a distance between the point of interest and the route, wherein the utility value is computed as a product of the affinity value and an inverse of the distance, and wherein the affinity value is generated based on a cluster analysis of transaction data associated with the user device;
wherein the selecting of the point of interest is further based on the utility value of the point of interest.
2. The method of claim 1 , wherein the utility value increases when the affinity value of the user for the location increases.
3. The method of claim 1 , further comprising:
computing utility values of a plurality of points of interests that are selected based on threshold distances of the points on the route, including the point of interest; and
ranking the plurality of points of interests according to the utility values, wherein the point of interest is selected based at least in part on a determination that the point of interest is ranked in a top portion of the plurality of points of interests that are ranked according to the utility values.
4. The method of claim 3 , further comprising:
selecting a portion of the route, wherein the distance between the point of interest and the route is a distance between the point of interest and selected portion of the route.
5. The method of claim 4 , wherein the selected portion of the route is based on an identification of an origin of the route.
6. The method of claim 4 , wherein the selected portion of the route is based on an identification of a destination of the route.
7. The method of claim 1 , wherein the identifying of the route of the user device comprises:
identifying locations on routes traversed by the user device;
assigning letters to the locations on the routes traversed by the user device;
connecting the letters representing the locations on the routes traversed by the user device according to the routes to generate route words for the routes;
storing the route words in a route dictionary having frequencies of the user device traversing the routes as usage frequencies of the route words;
detecting a set of locations on the route currently being traversed by the user device;
generating a leading route word portion from a sequence of letters representing the detected set of locations;
predicting a complete route word that has the leading route word portion using the route dictionary and based on the usage frequencies of the route words; and
identifying the route of the user device based on locations represented by letters in the complete route word.
8. The method of claim 1 , wherein the utility value is calculated by multiplying the affinity value by the inverse of the distance.
9. A computing apparatus, comprising:
at least one microprocessor; and
memory storing instructions configured to instruct the at least one microprocessor to at least:
identify a route of a user device having a plurality of segments defined by a set of locations on the route by identifying a sequence of letters corresponding to a set of locations of the user device and a complete word predicted based on the sequence of letters and a route dictionary;
for each respective point of a plurality of points on the route, compute a respective threshold distance from a predetermined function of:
a length of one of the plurality of segments on which the respective point is located; and
a predetermined distance;
select a point of interest for the route of the user device based at least in part on a determination that at least one of the points on the route has a threshold distance that is longer than a distance between the point of interest and the one of the points on the route;
transmit information related to the point of interest to the user device while the user device is on the route; and
compute a utility value of the point of interest based on an affinity value of the user device for the point of interest and a distance between the point of interest and the route, wherein the utility value is computed as a product of the affinity value and an inverse of the distance, and wherein the affinity value is based on transaction data associated with the user device;
wherein the point of interest is selected further based on the utility value of the point of interest.
10. The computing apparatus of claim 9 , wherein the utility value increases when the affinity value of the user for the location increases.
11. The computing apparatus of claim 9 , wherein the instructions are further configured to instruct the at least one microprocessor to:
compute utility values of a plurality of points of interests that are selected based on threshold distances of the points on the route, including the point of interest; and
rank the plurality of points of interests according to the utility values, wherein the point of interest is selected based at least in part on a determination that the point of interest is ranked in a top portion of the plurality of points of interests that are ranked according to the utility values.
12. The computing apparatus of claim 11 , wherein the instructions are further configured to instruct the at least one microprocessor to:
select a portion of the route, wherein the distance between the point of interest and the route is a distance between the point of interest and selected portion of the route.
13. The computing apparatus of claim 12 , wherein the selected portion of the route is based on an identification of an origin of the route.
14. The computing apparatus of claim 12 , wherein the selected portion of the route is based on an identification of a destination of the route.
15. The computing apparatus of claim 9 , wherein the instructions are further configured to instruct the at least one microprocessor to:
identify the route of the user device by:
identifying locations on routes traversed by the user device;
assigning letters to the locations on the routes traversed by the user device;
connecting the letters representing the locations on the routes traversed by the user device according to the routes to generate route words for the routes;
storing the route words in the route dictionary having frequencies of the user device traversing the routes as usage frequencies of the route words;
detecting the set of locations on the route currently being traversed by the user device;
generating a leading route word portion from the sequence of letters representing the detected set of locations;
predicting a complete route word that has the leading route word portion using the route dictionary and based on the usage frequencies of the route words; and
identifying the route of the user device based on locations represented by letters in the complete route word.
16. The computing apparatus of claim 9 , wherein the utility value is calculated by multiplying the affinity value by the inverse of the distance.
17. A non-transitory computer storage medium storing instructions configured to instruct a computing apparatus to perform a method, the method comprising:
identifying, by the computing apparatus, a route of a user device having a plurality of segments defined by a set of locations on the route;
for each respective point of a plurality of points on the route, computing, by the computing apparatus, a respective threshold distance from a predetermined function of:
a length of one of the plurality of segments on which the respective point is located; and
a predetermined distance;
selecting, by the computing apparatus, a point of interest for the route of the user device based at least in part on a determination that at least one of the points on the route has a threshold distance that is longer than a distance between the point of interest and the one of the points on the route; and
transmitting, by the computing apparatus, information related to the point of interest to the user device while the user device is on the route; and
computing a utility value of the point of interest based on an affinity value of the user device for the point of interest and a distance between the point of interest and the route, wherein the utility value is computed as a product of the affinity value and an inverse of the distance, and wherein the affinity value is generated based on a cluster analysis of transaction data associated with the user device;
wherein the point of interest is selected further based on the utility value of the point of interest.
18. The non-transitory computer storage medium of claim 17 , wherein the identifying of the route of the user device comprises:
identifying locations on routes traversed by the user device;
assigning letters to the locations on the routes traversed by the user device;
connecting the letters representing the locations on the routes traversed by the user device according to the routes to generate route words for the routes;
storing the route words in a route dictionary having frequencies of the user device traversing the routes as usage frequencies of the route words;
detecting a set of locations on the route currently being traversed by the user device;
generating a leading route word portion from a sequence of letters representing the detected set of locations;
predicting a complete route word that has the leading route word portion using the route dictionary and based on the usage frequencies of the route words; and
identifying the route of the user device based on locations represented by letters in the complete route word.
19. The non-transitory computer storage medium of claim 17 , wherein the utility value is calculated by multiplying the affinity value by the inverse of the distance.