CORRECTING INCONSISTENCIES IN SPATIO-TEMPORAL PREDICTION SYSTEM
An apparatus, method, and computer program product are disclosed for correcting inconsistencies in a spatio-temporal prediction system. A data module receives event-prediction data comprising a plurality of prediction probabilities. The plurality of prediction probabilities includes one or more ordering inconsistencies. A ranking module calculates one or more event-prediction rankings based on the event-prediction data while adjusting for the one or more ordering inconsistencies. A probability-ordering module orders the prediction probabilities based on the one or more event-prediction rankings.
1 . An apparatus comprising:
a data module configured to receive event-prediction data comprising a plurality of prediction probabilities, the plurality of prediction probabilities comprising one or more ordering inconsistencies;
a ranking module configured to calculate one or more event-prediction rankings based on the event-prediction data while adjusting for the one or more ordering inconsistencies; and
a probability-ordering module configured to order the prediction probabilities based on the one or more event-prediction rankings.
2 . The apparatus of claim 1 , further comprising a map module configured to present a map of an area associated with the event-prediction probabilities.
3 . The apparatus of claim 2 , wherein the area presented on the map is associated with one or more crimes, the event-prediction probabilities being derived from spatio-temporal data associated with the one or more crimes.
4 . The apparatus of claim 1 , further comprising an overlay module configured to overlay one or more hotspots on a map, the one or more hotspots indicating an area on the map that has a prediction probability above a predetermined threshold.
5 . The apparatus of claim 4 , wherein the overlay module further assigns a rank to the one or more hotspots according to the order of the prediction probabilities determined by the probability-ordering module.
6 . The apparatus of claim 4 , wherein the one or more hotspots are associated with one or more selected crimes, the one or more hotspots representing a likelihood of a near-repeat of a selected crime occurring in an area of the map associated with the hotspot.
7 . The apparatus of claim 1 , wherein the event-prediction probability data is derived from spatio-temporal data, the spatio-temporal data comprising one or more of a time and a location.
8 . The apparatus of claim 7 , wherein the spatio-temporal data comprises crime data, the crime data comprising a time of a crime and a location of a crime.
9 . The apparatus of claim 1 , wherein the plurality of prediction probabilities comprise real numbers that are arranged in a real matrix, the real matrix comprising one of an asymmetric matrix, a symmetric matrix, and a skew symmetric matrix.
10 . The apparatus of claim 1 , wherein the ranking module calculates the one or more event-prediction rankings using a discrete Helmholtz-Hodge decomposition.
11 . A method comprising:
receiving event-prediction data comprising a plurality of prediction probabilities, the plurality of prediction probabilities comprising one or more ordering inconsistencies;
calculating one or more event-prediction rankings based on the event-prediction data while adjusting for the one or more ordering inconsistencies; and
ordering the prediction probabilities based on the one or more event-prediction rankings.
12 . The method of claim 11 , further comprising presenting a map of an area associated with the event-prediction probabilities.
13 . The method of claim 12 , wherein the area presented on the map is associated with one or more crimes, the event-prediction probabilities being derived from spatio-temporal data associated with the one or more crimes.
14 . The method of claim 11 , further comprising overlaying one or more hotspots on a map, the one or more hotspots indicating an area on the map that has a prediction probability above a predetermined threshold.
15 . The method of claim 14 , further comprising assigning a rank to the one or more hotspots according to the order of the prediction probabilities determined by the probability-ordering module.
16 . The method of claim 14 , wherein the one or more hotspots are associated with one or more selected crimes, the one or more hotspots representing a likelihood of a near-repeat of a selected crime occurring in an area of the map associated with the hotspot.
17 . The method of claim 11 , wherein the event-prediction probability data is derived from spatio-temporal data, the spatio-temporal data comprising one or more of a time and a location.
18 . The method of claim 17 , wherein the spatio-temporal data comprises crime data, the crime data comprising a time of a crime and a location of a crime.
19 . The method of claim 11 , wherein the plurality of prediction probabilities comprise real numbers that are arranged in a real matrix, the real matrix comprising one of an asymmetric matrix, a symmetric matrix, and a skew symmetric matrix.
20 . A program product comprising a computer readable storage medium that stores code executable by a processor, the executable code comprising code to perform:
receiving event-prediction data comprising a plurality of prediction probabilities, the plurality of prediction probabilities comprising one or more ordering inconsistencies;
calculating one or more event-prediction rankings based on the event-prediction data while adjusting for the one or more ordering inconsistencies; and
ordering the prediction probabilities based on the one or more event-prediction rankings.