Samsung Electronics Co., Ltd.

Hae-jun Lee

Seung-hak Yu

Deok-ho Kim

Ho-jin Jung

Ji-hyun Rho

Tae-yeun Yang

Ha-yoon Jung

Eun-jeong Ko

Jung-wook Kim

Hui-won Yun

Hee-jun Song

Nilesh Kulkarni

Volodymyr Zubariev

Provided are an artificial intelligence (AI) system and an application thereof, which simulate functions of a human brain, such as recognition and determination, by using a machine learning algorithm, such as deep-learning. A method of processing, by a device, a keyboard input, based on training, may include: displaying a keyboard on a screen of the device; receiving a swipe input of a user, the swipe input connecting a plurality of keys on a displayed keyboard; extracting a trajectory connecting the plurality of keys; applying, to a trained model for a keyboard input, based on the trajectory, trajectory information indicating a shape of the trajectory and a relative position of the trajectory with respect to the keyboard; and determining at least one character corresponding to the trajectory, based on a result of the applying the trajectory information.

System and method of determining input characters based on swipe input

Provided is a device including a memory storing information about sequences of a plurality of registered words; an input unit comprising input circuitry configured to receive an input of a text comprising a first eojeol not belonging to the plurality of registered words, wherein, in the first eojeol, a first word is attached to a first registered word that belongs to the plurality of registered words; and a controller configured to detect the first registered word from the first eojeol, to determine a predicted eojeol to be input after the text, based on the information about the sequences of the plurality of registered words and the detected first registered word and to control a display to display the predicted eojeol.

Method and apparatus for recommending word

An example device for transmitting an answer message includes a display configured to display information, a communicator configured to receive a question message from another device, a processor configured to control the display to display graphics representing a plurality of pieces of recommendation information which are includable in an answer message for the received question message and relations between the plurality of pieces of recommendation information, and a user input unit configured to receive a user input that selects at least one of the plurality of pieces of recommendation information, wherein the communicator is further configured to transmit an answer message including the selected recommendation information to the another device according to the user input.

Answer message recommendation method and device therefor

A device for transmitting a reply message is provided. The device includes a communication unit configured to receive a question message from another device, a controller configured to determine a category of the question message, a display unit configured to display a user interface (UI) for selecting data to be included in a reply message to the question message, according to the category, and a user input unit configured to receive a user input of selecting data to be included in the reply message through the UI, wherein the communication unit transmits the reply message including the data to the other device.

Method and apparatus for recommending reply message

An electronic apparatus for compressing a language model is provided, the electronic apparatus including a storage configured to store a language model which includes an embedding matrix and a softmax matrix generated by a recurrent neural network (RNN) training based on basic data including a plurality of sentences, and a processor configured to convert the embedding matrix into a product of a first projection matrix and a shared matrix, the product of the first projection matrix and the shared matrix having a same size as a size of the embedding matrix, and to convert a transposed matrix of the softmax matrix into a product of a second projection matrix and the shared matrix, the product of the second projection matrix and the shared matrix having a same size as a size of the transposed matrix of the softmax matrix, and to update elements of the first projection matrix, the second projection matrix and the shared matrix by performing the RNN training with respect to the first projection matrix, the second projection matrix and the shared matrix based on the basic data.

Electronic apparatus for compressing language model, electronic apparatus for providing recommendation word and operation methods thereof

Provided are a device for transmitting an answer message including a display configured to display information, a communicator configured to receive a question message from another device, a processor configured to control the display to display graphics representing a plurality of pieces of recommendation information which are includable in an answer message for the received question message and relations between the plurality of pieces of recommendation information, and a user input unit configured to receive a user input that selects at least one of the plurality of pieces of recommendation information, wherein the communicator is further configured to transmit an answer message including the selected recommendation information to the another device according to the user input.

An electronic device and a method for controlling the electronic device are provided. The electronic device includes a communication interface configured to receive a message, at least one processor configured to determine a notification scheme for outputting the message based on status information about the electronic device and obtain a summary message by converting the message according to the notification scheme, and an output module for outputting the summary message.

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Suwon-si, South Korea

Hae-jun Lee