Computer-implemented method and device for text analysis

A computer-implemented method for training an artificial neural network using training data, which include features and identifiers, the features characterizing term candidates from a corpus, the corpus encompassing a text from a domain, each of the identifiers characterizing a degree of association to at least three classes for the term candidates that differ from one another, the different classes indicating different degrees of association of the term candidate to the domain, the training data including an assignment of the features to the identifiers, the method comprising the following steps:

• predefining a feature of the features to an input layer of the artificial neural network;
• assigning, by the artificial neural network, an identifier of the identifiers to the feature from the input layer in a prediction in an output layer of the artificial neural network;
• comparing the identifier from the output layer with the identifier assigned to the feature in the training data;
• and
• learning, as a function of the result of the comparison, at least one parameter of the artificial neural network, which characterizes a connection of the artificial neural network between the input layer and the output layer.

A computer-implemented method for generating training data for a training of an artificial neural network, the training data including features and identifiers, the method comprising the following steps:

• determining features which characterize term candidates from a corpus, the corpus including a text from a domain;
• determining a respective identifier which characterizes a degree of association to at least three classes for the term candidates that differ from one another, the different classes indicating different degrees of association of the term candidates to the domains;
• and
• assigning at least one of the identifiers to at least one of the features.