System, method and computer program product for path computing based on unpleasant data
First Claim
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1. A computer-implemented path computing method, the method comprising:
- extracting unpleasant data from a database to create a plurality of multi-variate spatio-temporal density functions;
collecting a tolerance level of a user; and
computing a path for the user based on the tolerance level and the plurality of density functions,wherein, around a geolocation of centroids defining an incident in the unpleasant data for each of the plurality of density functions, a decay function is created with decay rates that are weighted based on a type of the incident and a time of day associated with the incident, the decay being in relation to a distance from a location having a highest value risk of the unpleasant data,wherein a geofence is created around the centroids,wherein the computing determines a path between the geofences that does not overlap with the geofences to maximize a distance to the incidents in the centroids,wherein the computing entirely avoids the incident in the unpleasant data and maximizes a distance between each of the geolocation of centroids of the plurality of density functions, andwherein the path is computed based on a constrained optimization problem over a graph where locations are nodes in the geofence and the locations are connected using streets as edges in which an association between the tolerance level and the plurality of density functions are used to compute the path such that;
each edge of the geofence of the unpleasant data is less than the tolerance level;
a sum of the edge weights is minimized; and
a total time for the oath is less than a user time constraint.
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Abstract
A path computing method, system, and computer program product, include extracting unpleasant data from a database to create a multi-variate spatio-temporal density function, collecting a tolerance level of a user, and computing a path for the user based on the tolerance level and the density function.
11 Citations
17 Claims
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1. A computer-implemented path computing method, the method comprising:
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extracting unpleasant data from a database to create a plurality of multi-variate spatio-temporal density functions; collecting a tolerance level of a user; and computing a path for the user based on the tolerance level and the plurality of density functions, wherein, around a geolocation of centroids defining an incident in the unpleasant data for each of the plurality of density functions, a decay function is created with decay rates that are weighted based on a type of the incident and a time of day associated with the incident, the decay being in relation to a distance from a location having a highest value risk of the unpleasant data, wherein a geofence is created around the centroids, wherein the computing determines a path between the geofences that does not overlap with the geofences to maximize a distance to the incidents in the centroids, wherein the computing entirely avoids the incident in the unpleasant data and maximizes a distance between each of the geolocation of centroids of the plurality of density functions, and wherein the path is computed based on a constrained optimization problem over a graph where locations are nodes in the geofence and the locations are connected using streets as edges in which an association between the tolerance level and the plurality of density functions are used to compute the path such that; each edge of the geofence of the unpleasant data is less than the tolerance level; a sum of the edge weights is minimized; and a total time for the oath is less than a user time constraint. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A computer program product for path computing, the computer program product comprising a computer-readable storage medium having program instructions embodied therewith, the program instructions executable by a computer to cause the computer to perform:
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extracting unpleasant data from a database to create a plurality of multi-variate spatio-temporal density functions; collecting a tolerance level of a user; and computing a path for the user based on the tolerance level and the plurality of density functions, wherein, around a geolocation of centroids defining an incident in the unpleasant data for each of the plurality density functions, a decay function is created with decay rates that are weighted based on a type of the incident and a time of day associated with the incident, the decay being in relation to a distance from a location having a highest value risk of the unpleasant data, wherein a geofence is created around the centroids, wherein the computing determines a path between the geofences that does not overlap with the geofences to maximize a distance to the incidents in the centroids, wherein the computing entirely avoids the incident in the unpleasant data and maximizes a distance between each of the geolocation of centroids of the plurality of density functions, and wherein the path is computed based on a constrained optimization problem over a graph where locations are nodes in the geofence and the locations are connected using streets as edges in which an association between the tolerance level and the plurality of density functions are used to compute the path such that; each edge of the geofence of the unpleasant data is less than the tolerance level; a sum of the edge weights is minimized; and a total time for the path is less than a user time constraint. - View Dependent Claims (12, 13, 14, 15)
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16. A path computing system, said system comprising:
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a processor; and a memory, the memory storing instructions to cause the processor to; extract unpleasant data from a database to create a plurality of multi-variate spatio-temporal density functions; collect a tolerance level of a user; and compute a path for the user based on the tolerance level and the plurality of density functions, wherein, around a geolocation of centroids defining an incident in the unpleasant data for each of the plurality of density functions, a decay function is created with decay rates that are weighted based on a type of the incident and a time of day associated with the incident, the decay being in relation to a distance from a location having a highest value risk of the unpleasant data, wherein a geofence is created around the centroids, wherein the computing determines a path between the geofences that does not overlap with the geofences to maximize a distance to the incidents in the centroids, wherein the computing entirely avoids the incident in the unpleasant data and maximizes a distance between each of the geolocation of centroids of the plurality of density functions, and wherein the path is computed based on a constrained optimization problem over a graph where locations are nodes in the geofence and the locations are connected using streets as edges in which an association between the tolerance level and the plurality of density functions are used to compute the path such that; each edge of the geofence of the unpleasant data is less than the tolerance level; a sum of the edge weights is minimized; and a total time for the path is less than a user time constraint. - View Dependent Claims (17)
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Specification