| 摘要 |
The invention relates to a computer-implemented method of training a neural network, comprising: training a first neural network (4) of a self organizing map type with a first set (2) of first text documents (3) each containing one or more keywords (7) in a semantic context to map each document (3) to a point (X i /Y j ) in the self organizing map (5) by semantic clustering; determining, for each keyword (7) occurring in the first set (2), all points (X i /Y j ) in the self organizing map (5) to which first documents (3) containing said keyword (7) are mapped, as a pattern (6) and storing said pattern (6) for said keyword (7) in a pattern dictionary (9); forming at least one sequence (11) of keywords (7) from a second set (12) of second text documents (13) each containing one or more keywords (7) in a semantic context; translating said at least one sequence (11) of keywords (7) into at least one sequence (14) of patterns (6) by using said pattern dictionary (9); and training a second neural network (15) with said at least one sequence (14) of patterns (6). The invention further relates to computer-readable media and classification, prediction and translation machines based on neural networks. |
