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.
Please help me write a proper abstract based on the patent claims. CLAIM: 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.