Method and system for user based routing
A system and method for providing route information to a user, in which paths provided to the user are automatically selected based on personal information of the user, so that in following the provided paths, the user passes things in which the user may have particular interest.
1. A method of operating a system for providing personalized routing information to an end user in search of a product or product category, the method comprising:
in response to receiving a request to provide directions from a current location of the end user to a location of the product or product category identified by the end user,
calculating two or more routes from the current location to the location of the product or product category;
selecting, from the two or more routes, a particular number of the shortest routes;
assigning a score to each of the selected routes, wherein assigning comprises:
identifying a respective collection of products passed while traveling along each particular route of the selected routes from the current location to the location of the product or product category identified by the end user, and
calculating the score for each particular route, wherein the score for each particular route is representative of one or both of a likelihood of purchase by the end user of one or more of the products of the respective collection of products and a degree of relevancy of the one or more of the products to the product or product category identified by the end user; and
transmitting two or more of the selected routes to a communication device of the end user, according to the scores assigned to the selected routes.
2. The method according to claim 1 , wherein the likelihood of purchase by the end user of one or more of the products of the respective collection of products is determined using a collection of personal information of the end user.
3. The method according to claim 2 , wherein purchase history information from the collection of personal information is used to determine the likelihood of purchase by the end user of one or more of the products of the respective collection of products.
4. The method according to claim 2 , wherein demographic information derived from a video image of the end user is used to determine the likelihood of purchase by the end user of one or more of the products of the respective collection of products.
5. The method according to claim 4 , wherein the collection of personal information comprises the video image of the end user.
6. The method according to claim 2 , wherein personal information of a second end user is used to determine the likelihood of purchase by the end user of one or more of the products of the respective collection of products.
7. The method according to claim 6 , wherein the collection of personal information of the end user comprises the personal information of the second end user.
8. The method according to claim 1 , wherein the score assigned to a particular route is representative of a level of interest of the end user in things along the particular route.
9. The method according to claim 8 , wherein the particular route is a path through a store and the things are products for purchase.
10. A system for providing personalized routing information to an end user in search of a product or product category, the system comprising:
at least one processor communicatively coupled to a communication device of the end user, the at least one processor, during operation, at least:
in response to receiving a request to provide directions from a current location of the end user to a location of the product or product category identified by the end user,
calculating two or more routes from the current location to the location of the product or product category;
selecting, from the two or more routes, a particular number of the shortest routes;
assigning a score to each of the selected routes, wherein assigning comprises:
identifying a respective collection of products passed while traveling along each particular route of the selected routes from the current location to the location of the product or product category identified by the end user, and
calculating the score for each particular route, wherein the score for each particular route is representative of one or both of a likelihood of purchase by the end user of one or more of the products of the respective collection of products and a degree of relevancy of the one or more of the products to the product or product category identified by the end user; and
transmitting two or more of the selected routes to the communication device of the end user, according to the scores assigned to the selected routes.
11. The system according to claim 10 , wherein the likelihood of purchase by the end user of one or more of the products of the respective collection of products is determined using a collection of personal information of the end user.
12. The system according to claim 11 , wherein purchase history information from the collection of personal information is used to determine the likelihood of purchase by the end user of one or more of the products of the respective collection of products.
13. The system according to claim 11 , wherein demographic information derived from a video image of the end user is used to determine the likelihood of purchase by the end user of one or more of the products of the respective collection of products.
14. The system according to claim 13 , wherein the collection of personal information comprises the video image of the end user.
15. The system according to claim 11 , wherein personal information of a second end user is used to determine the likelihood of purchase by the end user of one or more of the products of the respective collection of products.
16. The system according to claim 15 , wherein the collection of personal information of the end user comprises the personal information of the second end user.
17. The system according to claim 10 , wherein the score assigned to a particular route is representative of a level of interest of the end user in things along the particular route.
18. The system according to claim 17 , wherein the particular route is a path through a store and the things are products for purchase.
19. A non-transitory computer-readable medium having a plurality of code sections, each code section comprising a plurality of instructions executable by one or more processors to perform actions that provide routing information to an end user moving between a current location and a location of a product or product category identified by the end user, the actions of the processor comprising:
in response to receiving a request to provide directions from a current location of the end user to the location of the product or product category identified by the end user,
calculating two or more routes from the current location to the location of the product or product category;
selecting, from the two or more routes, a particular number of the shortest routes;
assigning a score to each of the selected routes, wherein assigning comprises:
identifying a respective collection of products passed while traveling along each particular route of the selected routes from the current location to the location of the product or product category identified by the end user, and
calculating the score for each particular route, wherein the score for each particular route is representative of one or both of a likelihood of purchase by the end user of one or more of the products of the respective collection of products and a degree of relevancy of the one or more of the products to the product or product category identified by the end user; and
transmitting two or more of the selected routes to the communication device of the end user, according to the scores assigned to the selected routes.
20. The non-transitory computer-readable medium according to claim 19 , wherein the likelihood of purchase by the end user of one or more of the products of the respective collection of products is determined using a collection of personal information of the end user.
21. The non-transitory computer-readable medium according to claim 20 , wherein purchase history information from the collection of personal information is used to determine the likelihood of purchase by the end user of one or more of the products of the respective collection of products.
22. The non-transitory computer-readable medium according to claim 20 , wherein demographic information derived from a video image of the end user is used to determine the likelihood of purchase by the end user of one or more of the products of the respective collection of products.
23. The non-transitory computer-readable medium according to claim 22 , wherein the collection of personal information comprises the video image of the end user.
24. The non-transitory computer-readable medium according to claim 20 , wherein personal information of a second end user is used to determine the likelihood of purchase by the end user of one or more of the products of the respective collection of products.
25. The non-transitory computer-readable medium according to claim 24 , wherein the collection of personal information of the end user comprises the personal information of the second end user.
26. The non-transitory computer-readable medium according to claim 19 , wherein the score assigned to a particular route is representative of a level of interest of the end user in things along the particular route.
27. The non-transitory computer-readable medium according to claim 26 , wherein the particular route is a path through a store and the things are products for purchase.