DISTRIBUTING POINTS OF INTEREST

• US 20130007089A1
• Filed: 06/29/2011
• Published: 01/03/2013
• Est. Priority Date: 06/29/2011
• Status: Abandoned Application

• Current Assignee: Hewlett-Packard Development Company, L.P. (HP Inc.)
• Original Assignee: Hewlett-Packard Development Company, L.P. (HP Inc.)
• Inventors: O'Donnell, Cornelius J., Trask, James Bradford, Chunduri, Lakshmi Sri Jyothsna
• Application Number:
  US13/171,554
• Publication Number:
  US 20130007089A1
• Time in Patent Office: Days
• US Class Current: 709/201
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G09B 29/003 Maps
• CPC Class Codes: G09B 29/004 Map manufacture or repair; Tear or ink or water resistant maps; Long-life maps printing processes for maps B41M3/02; by permanently attaching map sections to sheets B42B7/00
• CPC Class Codes: G09B 29/007 using computer methods

Abstract

Example embodiments disclosed herein relate to distributing points of interest. One of multiple points of interest is determined based on a distance analysis of the points of interest. A cluster of the points of interest are determined. The points of interest of the cluster are distributed to map sets based on a statistical analysis.

Claims

1. A method comprising:

determining a plurality of points of interest at a device;

identifying one of the points of interest based on a distance analysis of the points of interest;

determining a cluster of the points of interest; and

distributing the points of interest within the cluster to a plurality of maps based on a statistical analysis.

2. The method of claim 1, further comprising:

determining, for each of the points of interest, respective numbers of the points of interest within a distance of other respective points of interest,

wherein the one point of interest is identified based on a determination that the number associated with the one point of interest is greater than or equal to the other respective numbers.

3. The method of claim 2, wherein the points of interest in the cluster are within the distance from the one point of interest.

4. The method of claim 1, wherein each of the points of interest of the cluster correspond to a horizontal coordinate and a vertical coordinate, the method further comprising:

determining a horizontal spread based on the vertical coordinates; and

determining a vertical spread based on the horizontal coordinates,

wherein the distribution of the points of interest of the cluster to the maps is based on the horizontal spread and the vertical spread.

5. The method of claim 4, further comprising:

determining a count of the maps based on a maximum number of the points of interest to associate with the respective maps.

6. The method of claim 5, further comprising:

determining a directional split based on the horizontal spread and the vertical spread,

wherein the count of the maps is split proportionately around the directional split.

7. The method of claim 6, further comprising:

determining that the count is odd; and

determining a weighting of the points of interest in relation to the directional split,

wherein a side of the directional split with a greater weighting has more of the maps than the other side of the directional split.

8. The method of claim 1, further comprising:

determining a set of the points of interest not included in the cluster;

identifying a first one of the points of interest of the set based on distance analysis of the points of interest in the set;

determining another cluster including the points of interest of the set that are within a particular distance of the first one set point of interest; and

distributing the points of interest of the other cluster to a plurality of other maps based on another statistical analysis.

9. The method of claim 1, further comprising:

determining the maps; and

generating book information including the maps with the respectively distributed points of interest and content respectively describing the distributed points of interest.

10. A device comprising:

a distance module to determine a distance between each of a plurality of points of interest with each of the other points of interest, wherein the points of interest are respectively associated with coordinates;

a selection module to select one point of interest from the points of interest;

a cluster module to determine a cluster of the points of interest that is within a predetermined distance of the one point of interest;

a map determination module to determine an amount of maps to distribute the cluster points of interest; and

a distribution module to distribute the cluster points of interest to a plurality of maps based on a statistical analysis.

11. The device of claim 10, wherein the respective coordinates of the cluster points of interest each include a horizontal coordinate and a vertical coordinate, the device further comprising:

a statistical analysis module to;

determine a horizontal standard deviation based on the vertical coordinates and a vertical standard deviation based on the horizontal coordinates, and

determine a split of the cluster points of interest based on the horizontal standard deviation and the vertical standard deviation,

wherein the distribution of the cluster points of interest to the maps is based on the split.

12. The device of claim 10, further comprising:

a book module to generate guide book information including the maps, wherein each map shows its distributed points of interest, the guide book information further comprising description information for each of the points of interest.

14. The non-transitory machine-readable storage medium of claim 12, further comprising instructions that, if executed by the processor, cause the processor to:

receive customization information, wherein the points of interest are determined based on the customization information; and

query map information from a map platform, wherein the map information includes one or more maps based on the map sets.

15. The non-transitory machine-readable storage medium of claim 14,

wherein the maps are respectively associated with a zoom-level,

wherein non-transitory machine-readable storage medium further comprises instructions that, if executed by the processor, cause the processor to:

determine that one or more of the points of interest not included in the set are within respective boundaries of the maps at the respective zoom-levels;

include the set and the one or more points of interest in an updated set;

determine a second horizontal spread based on the vertical coordinates associated with the points of interest of the updated set;

determine a second vertical spread based on the horizontal coordinates associated with the points of interest of the updated set; and

distribute the points of interest of the updated set to a plurality of other map sets based on a comparison of the second horizontal spread and the second vertical spread.

13. A non-transitory machine-readable storage medium storing instructions that, if executed by a processor of a device, cause the processor to:

determine a plurality of points of interest, wherein the respective points of interest are associated with respective horizontal coordinates and respective vertical coordinates;

determine a distance between each of the points of interest and each of the other points of interest;

identify one of the points of interest based on a number of the points of interest within a predetermined distance of the one point of interest;

select a set of the points of interest within the predetermined distance of the one point of interest;

determine a horizontal spread based on the vertical coordinates associated with the points of interest of the set;

determine a vertical spread based on the horizontal coordinates associated with the points of interest of the set; and

distribute the points of interest of the set into a plurality of map sets based on a comparison of the horizontal spread and the vertical spread.