Abstract: A method for managing memory for applications in a computing system includes receiving a selection of a preferred application. During user-controlled operation over the application, the transitions of selected application between foreground and background are monitored. A retention of the application in memory is triggered upon a transition of the application to background during the user operation. Retention of the application includes compressing memory portions of the application. Accordingly, the application is retained within the memory based on said compressed memory portions. A requirement to restore the retained application is sensed based on either a user selection or an automatically generated prediction and the application is restored from the retained state back to the foreground.

Abstract: A method for managing memory for applications in a computing system includes receiving a selection of a preferred application. During user-controlled operation over the application, the transitions of selected application between foreground and background are monitored. A retention of the application in memory is triggered upon a transition of the application to background during the user operation. Retention of the application includes compressing memory portions of the application. Accordingly, the application is retained within the memory based on said compressed memory portions. A requirement to restore the retained application is sensed based on either a user selection or an automatically generated prediction and the application is restored from the retained state back to the foreground.

Abstract: Provided is a method for predicting emotion of a user by an electronic device. The method includes receiving, by the electronic device, a user context, a device context and an environment context from the electronic device and one or more other electronic device connected to the electronic device and determining, by the electronic device, a combined representation of the user context, the device context and the environment context. The method also includes determining, by the electronic device, a plurality of user characteristics based on the combined representation of the user context, the device context and the environment context; and predicting, by the electronic device, an emotion of the user based on the combined representation of the user context, the device context, the environment context and the plurality of user characteristics.

Abstract: A method of generating structured relation information in an electronic device may include: classifying a first text input received by at least one application installed on the electronic device, into at least one category; extracting, from the first text input, a first entity representing a context of the first text input; generating structured relation information by associating the first entity extracted from the first text input, with a second entity extracted from at least one second text input stored in the electronic device or a server; and displaying the structured relation information on the electronic device.

Abstract: A method for intelligently sharing a content by an electronic device is provided. The method includes determining, by the electronic device, a context of sharing the content. The method includes analyzing, by the electronic device, the content with reference to the context. The method includes identifying, by the electronic device, portions of the content as non-shareable based on the analysis. The method includes providing, by the electronic device, a modification action suggestion on the portions identified as non-shareable.

Abstract: 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.

Abstract: A method of generating structured relation information in an electronic device may include: classifying a first text input received by at least one application installed on the electronic device, into at least one category; extracting, from the first text input, a first entity representing a context of the first text input; generating structured relation information by associating the first entity extracted from the first text input, with a second entity extracted from at least one second text input stored in the electronic device or a server; and displaying the structured relation information on the electronic device.

Abstract: A method for managing memory for applications in a computing system includes receiving a selection of a preferred application. During user-controlled operation over the application, the transitions of selected application between foreground and background are monitored. A retention of the application in memory is triggered upon a transition of the application to background during the user operation. Retention of the application includes compressing memory portions of the application. Accordingly, the application is retained within the memory based on said compressed memory portions. A requirement to restore the retained application is sensed based on either a user selection or an automatically generated prediction and the application is restored from the retained state back to the foreground.

Abstract: The present disclosure is related to the field of digital communication and provides a method and system for providing personalized multimodal objects in real-time. An object predicting system receives a text input from at least one application installed in a user device associated with a user. Thereafter, the object predicting system determines an intent of the user by analyzing the text input, which is then correlated with contextual data to generate a query. Subsequently, the object predicting system performs a unified search in a universal database, based on the query, wherein the universal database comprises multimodal data. Further, a plurality of multimodal objects predicted in response to the unified search are ranked based on at least one of the contextual data and user preferences. Finally, at least one of the predicted plurality of multimodal objected related to the text input are provided to the user based on the ranking.

Abstract: A method for determining sensitivity-based bias of text includes detecting an input action performed by a user from a plurality of actions, wherein the plurality of actions comprises typing one or more words on a virtual keyboard of a user device and accessing readable content on the user device. When the input action is accessing the readable content on the user device, determining the readable content to be insensitive by parsing the readable content and feeding the parsed readable content to a machine learning (ML) model, wherein the ML model is trained with insensitive datasets of an adversarial database, and presenting a first alert message on the user device before displaying the readable content completely on the user device when the readable content is determined to be insensitive.

Abstract: A method of generating structured relation information in an electronic device may include: classifying a first text input received by at least one application installed on the electronic device, into at least one category; extracting, from the first text input, a first entity representing a context of the first text input; generating structured relation information by associating the first entity extracted from the first text input, with a second entity extracted from at least one second text input stored in the electronic device or a server; and displaying the structured relation information on the electronic device.

Abstract: A method of user interaction in a wearable device with a curved periphery is provided. The method includes displaying a blob when an item is displayed on the screen of the wearable device, obtaining a first input on the curved periphery associated with the blob, obtaining a second input along the curved periphery in conjunction with the first input, and performing an action in the item displayed on the screen of the wearable device.

Abstract: A method of user interaction in a wearable device with a curved periphery is provided. The method includes displaying a blob when an item is displayed on the screen of the wearable device, obtaining a first input on the curved periphery associated with the blob, obtaining a second input along the curved periphery in conjunction with the first input, and performing an action in the item displayed on the screen of the wearable device.