Gong I.o Ltd.

Igal Grinis

Omri Allouche

Inbal Horev

Raquel Sitman

A system and method for generating a multi-label classifier of textual data is presented. The method includes training a plurality of single-label classifiers, wherein each of the plurality of single-label classifiers is trained to classify textual data to a single predefined revenue-based label; and training the multi-label classifier using labeled data output by the plurality of single-label classifiers, wherein the multi-label classifier is trained to classify textual data to a vector including revenue-based labels and their respective classification scores.

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Hod Hasharon, Israel

Igal Grinis