Samsung Electronics Co., Ltd.

Vibhav Agarwal

Barath Raj Kandur Raja

Ankur Agarwal

Yashwant Singh Saini

Srinivasa Rao Siddi

Mritunjai Chandra

Sreevatsa Dwaraka Bhamidipati

Hojun Jaygarl

Pilsik Choi

Vanraj Vala

Sriram Shashank

Raju Suresh Dixit

Naresh Purre

Seungseok Kang

Sri Lakshmi Punuru

Arjun Raj Kumar S

Arko Sabui

Himanshi Sinha

Sanguk Jeon

Himanshu Arora

Ketki Aniruddha Gupte

Rishabh Kumar

Dwakara Bhamidipati Sreevatsa

Kalyan Kakani

Likhith Amarvaj

Vipin Rao

Muthu Kumaran

Shweta Ratanpura

Sudeep Kumar Kodali

Harshavardhana Poojari

Hemant Tiwari

Shashank Sriram

Mansoor Variyathapara Mohammed

Bharath C

Aayush Yadav

Harshavardhana

Ishan Vaid

Manjunath Bhimappa Ujjinakoppa

Kranti Chalamalasetti

Jaehoon Park

Aditi Anil Kagane

Balaji Vijayanagaram Ramalingam

Ankita Bhardwaj

Example systems and methods provide input suggestions to a user to improve user experience on user devices. The input suggestions can be fill information from another app on device to the present app being used by user, information for performing a search (without the user having to copy-paste data or entering the data manually), responses to a message/notification received by the user, information/content/data to be shared between apps (without switching between apps), and emojis/GIFs that can be used by the user. The method includes analyzing one or more content of one or more screen displayed on device, generating at least one of a logical tree structure and a data mashup model of the one or more analyzed content for each screen, and providing a recommendation to a user. The recommendation can be a connected action or an input suggestion.

Systems and methods for smart capture to provide input and action suggestions

Methods and systems for predicting keystrokes using a neural network analyzing cumulative effects of a plurality of factors impacting the typing behavior of a user. The factors may include typing pattern, previous keystrokes, specifics of keyboard used for typing, and contextual parameters pertaining to a device displaying the keyboard and the user. A plurality of features may be extracted and fused to obtain a plurality of feature vectors. The plurality of feature vectors can be optimized and processed by the neural network to identify known features and learn unknown features that are impacting the typing behavior. Thereby, the neural network predicts keystrokes using the known and unknown features.

Methods and systems for predicting keystrokes using a unified neural network

An electronic device for providing contextual recommendations and a method therefor are provided. The electronic device includes a memory storing instructions, and at least one processor configured to execute the instructions to obtain text including characters, identify, based on a language model, a domain corresponding to the text, identify a reference of the characters based on the domain, and perform, based on the reference, an action related to the domain.

Contextual recommendation

An electronic device and a method for predicting a response are provided. The electronic device includes a display and a processor configured to receive at least one message, identify at least one contextual category of the at least one message, predict at least one response for the at least one message from a language model based on the at least one contextual category, and control the display to display the at least one predicted response.

Method and electronic device for predicting a response from context with a language model

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Bengaluru, India

Vibhav Agarwal