International Business Machines Corporation

Diego Matteo Antognini

Francesco Fusco

A computer implemented method, a computer program product and a computer system and are provided to enrich downstream learning tasks. A processor stores selected text terms from a corpus of text. A processor determines an initial set of specificity scores for the selected text terms to produce a set of training samples, where each of the training samples comprise a selected text term and an initial specificity score for the selected text term. A processor trains a character-based regression model with the set of training samples. A processor retrieves an Automated Term Extraction (ATE) training data set. A processor determines specificity scores for text terms included in the ATE training data set. A processor, responsive to respective specificity score for a text term in the ATE training data set being below a threshold value, masks the text term from being used in the ATE training data set.

Determining specificity of text terms in application contexts

An example system includes a processor to compute a token-level fingerprint for each of a number of tokens in a received window of text. The processor can compute a window representation for a window of text based on the token-level fingerprints. The processor can also update the window representation in a rolling scheme when sliding the window of text.

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Ruvigliana, Switzerland

Diego Matteo Antognini