Abstract: An electronic device and a method for controlling thereof are provided. The electronic device includes a display, a memory storing at least one instruction, and a processor, wherein the processor is configured to, by executing the at least one instruction, extract a plurality of texts displayed on a chat window of a message application and collect the texts, input the plurality of collected texts into a trained first neural network model and align the plurality of texts in order, input the plurality of texts aligned in order into a trained second neural network model and identify whether additional information for acquiring event information from the plurality of texts is necessary, and acquire event information from the plurality of texts based on the identification result.

Abstract: An electronic device and a method for controlling thereof are provided. The electronic device includes a display, a memory storing at least one instruction, and a processor, wherein the processor is configured to, by executing the at least one instruction, extract a plurality of texts displayed on a chat window of a message application and collect the texts, input the plurality of collected texts into a trained first neural network model and align the plurality of texts in order, input the plurality of texts aligned in order into a trained second neural network model and identify whether additional information for acquiring event information from the plurality of texts is necessary, and acquire event information from the plurality of texts based on the identification result.

Abstract: A control method of an electronic apparatus includes clustering words included in a plurality of domains respectively into a plurality of clustering groups based on information corresponding to the plurality of domains; obtaining an embedding vector between the words and the plurality of clustering groups based on learning data corresponding to respective domains, the words, and mass text learning data; and generating one or more final clustering groups of the words based on the obtained embedding vector and the plurality of clustering group.