Gong I.o Ltd.

Adi Kopilov

Omri Allouche

Inbal Horev

Eyal Ben David

A system and method for a multi-stage approach for creating topic models is presented. The method includes applying a first stage topic model to textual data, wherein the first stage topic model is trained to discover a first plurality of topics and distributions of words in each topic of the first plurality of topics from the textual data; generating at least one seeded word for a subset of topics of the first plurality of topics, wherein the at least one seeded word is determined based on a plurality of selection rules and the distributions of words in the subset of topics discovered in the first stage topic model; and creating a second stage topic model by feeding the generated at least one seeded word to direct identification of the subset of topics of the first plurality of topics.

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Tel Aviv, Israel

Adi Kopilov