Abstract:
A weather forecast system, method of forecasting weather and a computer program product therefor. A forecasting computer applies a grid to a forecast area and provides a weather forecast for each grid cell. Population movement sensors sense population movement in the area. A swarm detector detects patterns in area population movement that indicate swarm activity, from which the swarm detector predicts swarm patterns. A planning module receives area weather forecasts and swarm patterns, and provides swarm path indications to the forecasting system for adjusting the grid applied to the forecast area.
Abstract:
A computer implemented method, system, and product for finding correspondence between terms in two different languages. The method includes the steps of: creating a technical term set and a general term set for each of i) a first language and ii) a second language, creating two bipartite graphs, where each graph corresponds to one of the two languages, and connects the technical term set and general term set of each language, respectively, with weighted links based on corpus information, creating a third bipartite graph by creating weighted links between general terms in the first language and general terms in the second language by using a translation dictionary, creating an association matrix M corresponding to the three bipartite graphs, calculating a similarity matrix Q by calculation of an inverse matrix, and outputting correspondence between the technical term sets of the first and second language on basis of the similarity matrix.
Abstract:
A computer implemented method, system, and product for finding correspondence between terms in two different languages. The method includes the steps of: creating a technical term set and a general term set for each of i) a first language and ii) a second language, creating two bipartite graphs, where each graph corresponds to one of the two languages, and connects the technical term set and general term set of each language, respectively, with weighted links based on corpus information, creating a third bipartite graph by creating weighted links between general terms in the first language and general terms in the second language by using a translation dictionary, creating an association matrix M corresponding to the three bipartite graphs, calculating a similarity matrix Q by calculation of an inverse matrix, and outputting correspondence between the technical term sets of the first and second language on basis of the similarity matrix.
Abstract:
A weather forecast system, method of forecasting weather and a computer program product therefor. A forecasting computer applies a grid to a forecast area and provides a weather forecast for each grid cell. Population movement sensors sense population movement in the area. A swarm detector detects patterns in area population movement that indicate swarm activity, from which the swarm detector predicts swarm patterns. A planning module receives area weather forecasts and swarm patterns, and provides swarm path indications to the forecasting system for adjusting the grid applied to the forecast area.
Abstract:
A computer implemented method, system, and product for finding correspondence between terms in two different languages. The method includes the steps of: creating a technical term set and a general term set for each of i) a first language and ii) a second language, creating two bipartite graphs, where each graph corresponds to one of the two languages, and connects the technical term set and general term set of each language, respectively, with weighted links based on corpus information, creating a third bipartite graph by creating weighted links between general terms in the first language and general terms in the second language by using a translation dictionary, creating an association matrix M corresponding to the three bipartite graphs, calculating a similarity matrix Q by calculation of an inverse matrix, and outputting correspondence between the technical term sets of the first and second language on basis of the similarity matrix.
Abstract:
A computer implemented method, system, and product for finding correspondence between terms in two different languages. The method includes the steps of: creating a technical term set and a general term set for each of i) a first language and ii) a second language, creating two bipartite graphs, where each graph corresponds to one of the two languages, and connects the technical term set and general term set of each language, respectively, with weighted links based on corpus information, creating a third bipartite graph by creating weighted links between general terms in the first language and general terms in the second language by using a translation dictionary, creating an association matrix M corresponding to the three bipartite graphs, calculating a similarity matrix Q by calculation of an inverse matrix, and outputting correspondence between the technical term sets of the first and second language on basis of the similarity matrix.