Determining points of interest using intelligent agents and semantic data

• US 8,543,586 B2
• Filed: 11/24/2010
• Issued: 09/24/2013
• Est. Priority Date: 11/24/2010
• Status: Expired due to Fees

• Current Assignee: AirBNB Incorporated
• Original Assignee: International Business Machines Corporation
• Inventors: Ramanathan, Sri, Terry, Matthew A., Trevathan, Matthew B., Glachant, Mathieu J. R., Jenkins, Alvin
• Primary Examiner(s): Truong, Dennis
• Application Number:
  US12/954,298
• Publication Number:
  US 20120131028A1
• Time in Patent Office: 1,035 Days
• Field of Search: 707/758, 707/707, 707/736, 707/722, 455/456.1, 382/100, 382/190, 382/154, 382/224, 701/530, 701/445, 701/461, 701/532
• US Class Current: 707/758
• CPC Class Codes: G06F 16/29 Geographical information databases
• CPC Class Codes: G06F 16/3344 using natural language analysis
• CPC Class Codes: H04W 4/02 Services making use of location information
• CPC Class Codes: H04W 4/029 Location-based management or tracking services

Abstract

A method, a system, and a computer program product are provided for determining points of interest using intelligent agents and semantic data. The method is implemented in a computer infrastructure having computer executable code tangibly embodied on a computer readable storage medium having programming instructions operable for receiving a media data comprising a location data comprising where media was captured. The instructions are also operable for determining at least one point of interest based on the media data, tying the media data to the at least one point of interest, and providing the media data tied to the at least one point of interest to an end user.

Claims

1. A method implemented in a computer infrastructure having computer executable code tangibly embodied on a computer readable storage medium having programming instructions operable for:

receiving media data comprising location data comprising where media was captured;

determining a center of a cluster of the media, comprising;

plotting the media as data points on a map using the location data;

determining whether a number of the data points in a defined array on the map is greater than a predetermined number; and

determining a center of the number of the data points as the center of the cluster of the media when the number is greater than the predetermined number, wherein the determining the center of the number of data points comprises weighting or deteriorating each data point of the media with a weight “

d”

by multiplying the location data of the media by “

d”

, and calculating the center of the cluster of the media using the weighted location data determined for each media;

determining at least one point of interest based on the media data and the center of the cluster of the media;

tying the media data to the at least one point of interest; and

providing the media data tied to the at least one point of interest to an end user.

2. The method of claim 1, wherein the media data further comprises a direction data comprising a direction a device was pointing to capture the media.

3. The method of claim 2, wherein the determining the center of the cluster of the media comprises:

determining an azimuth-based center of the cluster of the media based on an intersection of the direction data when the number is greater than the predetermined number; and

determining the at least one point of interest based on the azimuth-based center.

4. The method of claim 1, wherein the determining the center of the cluster of the media comprises:

determining a geographic center of the cluster of the media based on an average midpoint of the weighted location data when the number is greater than the predetermined number; and

determining the at least one point of interest based on the geographic center.

5. The method of claim 4, wherein the determining of the at least one point of interest based on the geographic center comprises:

plotting a predetermined area around the geographic center; and

determining whether at least one current point of interest falls within the predetermined area.

6. The method of claim 1, wherein the determining of the at least one point of interest comprises:

determining a semantic data based on the media data; and

determining the at least one point of interest based on the semantic data.

7. The method of claim 1, wherein the determining of the at least one point of interest comprises:

determining at least one current point of interest based on the media data; and

determining the at least one point of interest based on the at least one current point of interest.

8. The method of claim 1, further comprising tying the media data to a semantic data related to the at least one point of interest, wherein the tying the media data to the semantic data comprises:

determining a level of confidence that the media data is related to the semantic data; and

inferring the media data is related to the semantic data if the level of confidence is greater than or equal to a predetermined threshold.

9. The method of claim 1, wherein the tying the media data to the at least one point of interest comprises tagging the media with the at least one point of interest.

10. The method of claim 1, wherein a service provider at least one of creates, maintains, deploys and supports the computer infrastructure.

11. The method of claim 1, wherein steps of claim 1 are provided by the service provider on a subscription, advertising, and/or fee basis.

24. The method of claim 1, further comprising determining distances between the media, and determining whether any of the media is outside of the cluster of the media based on the distances.

25. The method of claim 1, wherein the weighted factor “

d”

is 365 minus a number of days that have passed since the media was entered or uploaded.

12. A system implemented in hardware, comprising:

a media agent configured to receive media data comprising location data of where media was captured;

a center agent configured to;

determine a center of a cluster of the media, comprising;

plotting the media as data points on a map using the location data;

determine whether a number of the data points in a defined array on the map is greater than a predetermined number; and

determine a center of the number of the data points as the center of the cluster of the media data when the number is greater than the predetermined number, wherein the determining the center of the number of data points comprises weighting or deteriorating each data point of the media with a weight “

d”

by multiplying the location data of the media by “

d”

, and calculating the center of the cluster of the media using the weighted location data determined for each media; and

an arbiter module configured to;

receive the media data from the media agent;

receive the center of the cluster of the media from the center agent;

determine at least one point of interest based on the media data and the center of the cluster of the media;

tie the media data to the at least one point of interest;

receive from an end user a request for the media related to the at least one point of interest; and

provide the user at least one of another media and another media data tied to the at least one point of interest.

13. The system of claim 12, wherein:

the media data further comprises a direction data comprising a direction a device was pointing to capture the media;

the center agent is an azimuth-based center agent configured to determine an azimuth -based center of the cluster of the media based on an intersection of the direction data when the number is greater than the predetermined number; and

the arbiter module is further configured to;

receive the azimuth-based center from the azimuth-based center agent; and

determine the at least one point of interest based on the azimuth-based center.

14. The system of claim 12, wherein the center agent is a geographic center agent configured to determine a geographic center of the cluster of the media based on an average midpoint of the weighted location data when the number is greater than the predetermined number,

wherein the arbiter module is further configured to:

receive the geographic center from the geographic center agent; and

determine the at least one point of interest based on the geographic center.

15. The system of claim 12, further comprising a semantic data agent configured to determine a semantic data based on the media data,

wherein the arbiter module is further configured to:

receive the semantic data from the semantic data agent; and

determine the at least one point of interest based on the semantic data.

16. The system of claim 12, further comprising a current points of interest agent configured to determine at least one current point of interest based on the media data,

wherein the arbiter module is further configured to:

receive the at least one current point of interest from the current points of interest agent; and

determine the at least one point of interest based on the at least one current point of interest.

17. The system of claim 12, wherein the arbiter module is further configured to tie the media data to semantic data related to the at least one point of interest.

18. The system of claim 12, wherein the arbiter module is further configured to:

search for a file comprising the at least one point of interest and a location where the another media was captured, from a plurality of files comprising points of interests and locations where media related to the points of interests were captured;

read the location from the file; and

search for the at least one of the another media and the another media data based on the location.

19. A computer program product comprising a computer readable storage medium having readable program code embodied in the storage medium, the computer program product includes at least one component operable to:

receive media data comprising location data comprising where media was captured;

determine a center of a cluster of the media, comprising;

plotting the media as data points on a map using the location data;

providing a grid and an array on the map, the array representing a number of units on the grid;

determine whether a number of the data points in the array on the map is greater than a predetermined number; and

determine a center of the number of the data points as the center of the cluster of the media data when the number is greater than the predetermined number, wherein the determining the center of the number of data points comprises weighting or deteriorating each data point of the media with a weight “

d”

by multiplying the location data of the media by “

d”

, where “

d”

is a predetermined amount of time minus a number of days that have passed since the media was entered or uploaded to the system, and calculating the center of the cluster of the media using the weighted location data determined for each media;

determine at least one point of interest based on the media data and the center of the cluster of the media;

tie the media data to the at least one point of interest;

determine a file based on the media data tied to the at least one point of interest; and

provide the file for at least one of a presentation to an end user, tagging the media, and storage.

20. The computer program product of claim 19, wherein the media data further comprises a direction data comprising a direction a device was pointing to capture the media.

21. A method of deploying a system for identifying at least one point of interest, comprising:

providing a computer infrastructure, being operable to;

receive media data comprising location data comprising where media was captured;

determine a center of a cluster of the media, comprising;

plotting the media as data points on a map using the location data;

providing a grid and an array on the map, the array representing a number of units on the grid;

determine whether a number of the data points in the array on the map is greater than a predetermined number; and

determine a center of the number of the data points as the center of the cluster of the media data when the number is greater than the predetermined number, wherein the determining the center of the number of data points comprises weighting or deteriorating each data point of the media with a weight “

d”

by multiplying the location data of the media by “

d”

, where “

d”

is a predetermined amount of time minus a number of days that have passed since the media was entered or uploaded to the system. and calculating the center of the cluster of the media using the weighted location data determined for each media;

determine the at least one point of interest based on the media data and the center of the cluster of the media;

tie the media data to the at least one point of interest; and

provide the media data tied to the at least one point of interest to an end user.

22. The method of claim 21, wherein the media data further comprises a direction data comprising a direction a device was pointing to capture the media.

23. A computer system for determining points of interest, the system comprising:

a CPU, a computer readable memory and a computer readable storage media;

first program instructions to receive media data comprising location data of where media was captured and a direction data comprising a direction a device was pointing at to capture the media;

second program instructions to determine a center of a cluster of the media, comprising;

plotting the media as data points on a map using the location data;

providing a grid and an array on the map, the array representing a number of units on the grid;

determine whether a number of the data points in the array on the map is greater than a predetermined number; and

determine a center of the number of the data points as the center of the cluster of the media data when the number of the data points is greater than the predetermined number, wherein the determining the center of the number of data points comprises weighting or deteriorating each data point of the media with a weight “

d”

by multiplying the location data of the media by “

d”

, where “

d”

is a predetermined amount of time minus a number of clays that have passed since the media was entered or uploaded to the system, and calculating the center of the cluster of the media using the weighted location data determined for each media;

third program instructions to determine at least one point of interest based on the media data and the center of the cluster of the media data;

fourth program instructions to tie the media data to the at least one point of interest; and

fifth program instructions to provide the media data tied to the at least one point of interest to an end user,

wherein the first-fifth program instructions are stored on the computer readable storage media for execution by the CPU via the computer readable memory,

wherein second program instructions are further configured to;

determine an azimuth-based center of the cluster of the media based on an intersection of the direction data when the number of the data points is greater than the predetermined number;

determine a geographic center of the cluster of the media based on an average midpoint of the weighted location data when the number of the data points is greater than the predetermined number;

determine semantic data based on the media data;

determine at least one current point of interest based on the media data; and

determine the at least one point of interest based on the azimuth-based center, the geographic center, the semantic data, and the at least one current point of interest.