Methods and system for providing information selected from a large set of digital content to at least one user. One such method comprises receiving user context information associated with the at least one user and identifying or generating, using at least one processor executing stored program instructions, a first concept in a semantic network, the first concept representing at least a portion of the user context information. The method further comprises obtaining at least one concept, including a second concept, semantically relevant to the first concept at least in part, by synthesizing the second concept based on the first concept and at least one other concept in the semantic network; and providing information to the at least one user, wherein the information is selected by using the first concept and the at least one obtained concept semantically relevant to the first concept, wherein the first concept in a semantic network is represented by a data structure storing any data associated with a node in the semantic network.

The present application describes a system (100) and method for detecting and labeling structures of interest. The system includes a current patient study database (102) containing a current patient study (200) with clinical contextual information (706). The system also includes an image metadata processing engine (118) configured to extract metadata for preparing an input for an anatomical structure classifier (608), a natural language processing engine (120) configured to extract clinical context information (706) from the prior patient documents, an anatomical structure detection and labeling engine (718), and a display device (108) configured to display findings from the current patient study. The anatomical structure detection and labeling engine (718) is configured to identify and label one or more structures of interest (716) from the extracted metadata and clinical context information (706). The processor (112) is also configured to aggregate series level data. The method detects, label and prioritize anatomical structures (710). Specifically, once patient information is received from the current patient study (108), the labeled anatomical structures (710) and the high risk anatomical structures (714) are combined to form an optimized prioritized list of structures of interest (716).

An augmented computer keyboard for inputting text into a computer is provided, where each character of the text being input is displayed on a computer screen in real time. The computer keyboard preferably has a QWERTY key layout, and has at least two additional keys which have selection functionality to select one or another of suggested text strings appearing in selected display fields on the computer screen. There is one display field for each provided additional key. The suggested text strings are presented in the respective selected display fields dynamically and in real time as each keystroke is made, and are chosen using predictive text software running on the computer. In a preferred embodiment, the additional keys are physically placed so as to be near the space bar on the computer keyboard.

A method, device and terminal for implementing regional screen capture are described. The method includes: capturing a full content of a current screen interface according to a screen capture instruction and generating a picture; parsing layout information of the current screen interface, and mark various controls in the generated picture by using the acquired layout information; determining a capture region according to a control selected based on a mark, and capturing the content displayed on one or more determined capture regions; when the capture is required, capturing the full content of the current screen interface and generating picture data; parsing the layout information of the current screen interface, and marking various controls on the generated picture according to the acquired layout information; and determining the capture region according to the selected controls.

An intention inference system includes, a morphological analyzer to perform morphological analysis for a complex sentence with multiple intentions involved, a syntactic analyzer to perform syntactic analysis for the complex sentence morphologically analyzed by the morphological analyzer and to divide it into the first simple sentence and the second simple sentence, an intention inference unit to infer the first intention involved in the first simple sentence and the second intention involved in the second simple sentence, a feature extractor to extract as the first feature a morpheme showing execution order of operations involved in the first simple sentence and to extract as the second feature a morpheme showing execution order of operations involved in the second simple sentence, and an execution order inference unit to infer the execution order of the first operation corresponding to the first intention and the second operation corresponding to the second intention on the basis of the first feature and the second feature extracted by the feature extractor. This enables the system to infer user's intentions accurately.

When the number of characters displayable on a character display area of a display is restricted, the information providing system generates a first recognition object word from information of object to be provided. At the same time, the information providing system generates a second recognition object word by using whole of a character string which is obtained by shortening the first recognition object word to have the specified character number when its number of characters exceeds a specified character number, to thereby recognize a speech voice by a user, using the first recognition object word and the second recognition object word.

Methods, systems, and apparatus for receiving user input that invokes digital assistant functionality; obtaining screen data indicating content displayed on a screen of the computing device; determining a classification for an entity referenced in the content indicated by the screen data; determining a suggested request that refers to the entity based on the determined classification; and providing the suggested request in response to receiving the user input that invokes the digital assistant functionality.

Computer-implemented techniques can include obtaining, by a computer server having one or more processors, a phonetics-based character mapping between a source script and a different target script, the phonetics-based character mapping relating characters in the source and target scripts that have similar sounds or pronunciations. The techniques can include encoding, by the computer server, each character of the phonetics-based character mapping using an encoding scheme to obtain an encoded character mapping, wherein the encoding scheme is common to both the source and target scripts. The techniques can include generating, by the computer server, a mapping function that directly maps encoded source script characters to encoded target script characters in the encoded character mapping. The techniques can also include in response to a transliteration request, utilizing, by the computer server, the mapping function to transliterate a text from the source script to the target script.

The techniques described herein are directed to robust matching for identity screening. In some examples, the techniques can include generating a similarity score for received identity information compared to a reference record. In some examples, the techniques can utilize a region associated with the received identity information to weight tokens composing the identity information or of the reference record to adjust the similarity score. Moreover, the techniques can include multiple tokenizers, transformation providers, and token weight providers and the techniques can be configured to select between the multiple tokenizers, transformation providers, and token weight providers based at least in part on a region to improve the accuracy of the similarity score. The techniques can determine whether or not to flag or otherwise affirm an identity of an individual or entity associated with the entity information based at least in part on the similarity score.

The present invention relates to an in-browser editor. Specifically, embodiments of the present invention provide a system and method of editing content in a browser without having to rely on the particular in-browser editing technology, such as “contentEditable” and “innerHTML.” The system includes a parser that converts an input string representing content edits in the browser into a data structure known as an Intermediary DOM (document object model). The Intermediary DOM provides a completely accurate representation of editor content in real time and operates in tandem with the Browser DOM to render the edited content in the Intermediary DOM back into displayable content.