Disclosed methods and systems are directed to concept identification and capture. The methods and systems may include receiving, by a device, a first natural language input comprising one or more terms, and analyzing the first natural language input via a natural language processing engine to identify one or more named entities associated with the one or more terms, wherein each of the one or more named entities is associated with at least one category of a plurality of categories. The methods and systems may also include detecting a text field configured to receive text, the text field being associated with one of the plurality of categories, and inputting into the text field one of the one or more identified named entities based on the text field being associated with a same category as the one of the one or more named entities.

A method and a system for providing an extract document from a source document, the source document being a classified document, the method including the steps of: a) providing the source document in a computer readable format, selecting at least one item from the source document, establishing an identifying data set to identify the at least one item that has been selected, validating the at least one item that has been selected, e) providing the extract document in a fixed format by performing an irreversible conversion of the source document, based on the source document and the identifying data set for the at least one item that has been validated.

Automatic quotes or references are generated based on a user's interaction with one or more pieces of content. A passage for quotation may be determined based at least in part on usage data including information about interaction with one or more pieces of content. A user may begin to type a quotation and a corresponding passage is inserted. The user may vary the scope of the passage, such as adding sentences or paragraphs. User annotation of the passage while the content is presented may also generate an automatically inserted quotation. A citation descriptive of the quoted passage may also be inserted. The automatically inserted quotation may be configured with a link or script, allowing additional functions or access to source content.

Disclosed herein are system, apparatus, article of manufacture, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for automatically determining the functionality and capabilities of electronic components. Some embodiments operate by transmitting a command to the display device in question (sometimes called the device under testDUTherein) and monitoring the device. Then, it is determined whether an action by the display device was one of a set of proper responses to the command. If the action was proper, then it is determined that the display device supports the command set associated with the command. The command set may be the Consumer Electronics Control (CEC) set, although this disclosure is not limited to that example.

An example method involves (i) accessing first data representing text, wherein the text defines at least one position representing a particular type of grammatical break between two portions of the text; (ii) identifying, from among the at least one position, a position that is closest to a target position within the text; (iii) based on the identified position within the text, generating second data that represents a proper subset of the text, wherein the proper subset extends from an initial position within the text to the identified position within the text; and (iv) providing output based on the generated second data.

Examples described herein generally relate to a computer device including display, a memory, and at least one processor configured to render content modules to the display. The processor determines a display size of the display on which the content is to be rendered. The processor determines a priority of each of the multiple content modules. The processor determines, for each content module, display capabilities including one or more numbers of columns that the content module can span at the display size. The processor scores each layout of a first set of multiple layouts of the multiple content modules based on at least a priority, a number of columns, and unused space of the layout. The processor generates instructions for rendering the multiple content modules to the display at the display size according to the one layout of the multiple layouts with a best score.

A computer-implemented method for matching user inputted text to stored text. The user inputted text is compared to each of the text strings stored in a database using a Levenshtein distance algorithm. For each comparison, the Levenshtein distance is analyzed to determine exact matches, non-matches, and probable matches. Probable matches are further analyzed using a keyboard distance algorithm to differentiate between matches and non-matches.

Embodiments of the present application relate to a method for displaying a web page, a system for displaying a web page, and a computer program product for displaying a web page. A method for displaying a web page is provided. The method includes pre-processing text information to be picture processed in a web page, creating a picture, generating a position description for each text block in the picture, filling the corresponding text blocks into the picture based on the position descriptions, generating a call address for the picture, and correspondingly saving the call address and the position description of each text block as metadata. If an access request for the web page is received, invoking the metadata, loading the picture, selecting at least one corresponding text block from the picture, and displaying the at least one text block is performed.

An input method editor (IME) is associated with a local user. Memory stores local data and a processor, coupled to the memory, is configured to receive input from a local, first user, obtain shared data associated with at least a remote, second user from a remote server and generate prediction candidates and conversion candidates based on the input provided by the local, first user and correlation of the input and the obtained shared data.

A computer-implemented method for matching user inputted text to stored text. The user inputted text is compared to each of the text strings stored in a database using a Levenshtein distance algorithm. For each comparison, the Levenshtein distance is analyzed to determine exact matches, non-matches, and probable matches. Probable matches are further analyzed using a keyboard distance algorithm to differentiate between matches and non-matches.