Patent ID: 9292800
Filing Date: 2016-03-22
CPC Classification: G06N,G06Q,G08G

Claim Text:
1. A method of predicting the origin and destination points of an unknown trip using a computer, the method comprising: receiving an input of second marker information including the type and position of a known marker included in a second region; generating a second feature vector at each spot included in the second region on the basis of the second marker information; and predicting the probability that the respective spots included in the second region are the origin and destination points on the basis of a prediction model, which is acquired based on first marker information including the type and position of a known marker included in a first region and information on the known origin and destination points included in the first region, and the second feature vector, wherein the prediction model is modeled on the assumption that probability that n is the number of trips where the spot is the origin or destination conforms to the Poisson distribution, with respect to each spot, and wherein the prediction model learning further includes: receiving an input of the first marker information including the type and position of the known marker included in the first area; and generating the first feature vector at each spot included in the first region on the basis of the first objective information, and wherein the prediction model linearly approximates the logarithm of a parameter μ of the Poisson distribution by using the first feature vector.