US 12,292,932 B2
Fast and accurate geomapping
Dakshi Agrawal, Monsey, NY (US); Raghu K. Ganti, Elmsford, NY (US); Mudhakar Srivatsa, White Plains, NY (US); and Petros Zerfos, New York, NY (US)
Assigned to INTERNATIONAL BUSINESS MACHINES CORPORATION, Armonk, NY (US)
Filed by INTERNATIONAL BUSINESS MACHINES CORPORATION, Armonk, NY (US)
Filed on Jan. 6, 2023, as Appl. No. 18/150,950.
Application 18/150,950 is a continuation of application No. 14/230,676, filed on Mar. 31, 2014, granted, now 11,586,680.
Prior Publication US 2023/0161822 A1, May 25, 2023
This patent is subject to a terminal disclaimer.
Int. Cl. G06F 16/00 (2019.01); G06F 16/29 (2019.01); G06F 16/901 (2019.01); G06F 16/903 (2019.01)
CPC G06F 16/90344 (2019.01) [G06F 16/29 (2019.01); G06F 16/9014 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method for discovering k-nearest-neighbors to a given object represented by a point within a certain linear, one-dimensional distance d, comprising:
obtaining an indexed set of geometries, and pruning a space of possible objects by gradually removing characters from one or more geocodes, the pruning enabling geomapping of the object represented by the point and minimizing a number of distance calculations by utilizing adaptive resolution properties of geohash;
calculating a geohash representation of the point with an adaptive resolution equal to a magnitude value of the certain linear, one-dimensional distance d, the calculating the geohash representation including determining a number of bits needed to encode accuracy of the distance d using the geohash representation;
searching for a closest-prefix geometry from the indexed set of geometries using the geohash representation of the point to identify all objects including at least a number of bits needed to encode accuracy of the distance d using the geohash representation;
calculating linear, one-dimensional distances between the point and geometries identified from the indexed set of geometries that have a same prefix as the closest-prefix geometry; and
determining k geometries with respective shortest linear, one-dimensional distances less than d from the geometries identified from the indexed set of geometries that have the same prefix as the closest-prefix geometry.