A system and method for managing electronic social networking includes defining content from a first user for communication to other users on an electronic social networking system. Natural language processing (NLP) and analytic analysis are applied to the content to identify a workflow for accessing and responding to the content. The access and the response to the content are based on the workflow.

A technique for ordering textual messages in a graphical user interface (GUI) of a communication application based on text content can include receiving a textual message, and determining an insertion point in the GUI based on the text content of the received textual message. In some implementations, determining the insertion point can include utilizing a language model to determine a probability that the text content of the textual message is associated with each preceding textual message. Additionally or alternatively, determining an insertion point can include utilizing a timestamp corresponding to a time that the received textual message was initiated by a sender user. The technique can further include displaying the textual message at the determined insertion point of the GUI. In some implementations, the displaying of the textual message can include providing an active indication of the received textual message being inserted at the determined insertion point.

A mechanism is provided in a data processing system for identifying nonsense passages in documents being ingested into a corpus. A natural language processing pipeline configured to execute in the data processing system receives an input document to be ingested into a corpus. The natural language processing pipeline divides the input document into a plurality of input passages. A filter component of the natural language processing pipeline identifies whether each input passage is a nonsense passage based on a value of a metric determined according to a set of feature counts. The natural language processing pipeline filters each input passage in the plurality of input passages based on whether the input passage is identified as a nonsense passage or not identified as a nonsense passage to form a filtered plurality of input passages. The natural language processing pipeline adds the filtered plurality of input passages into the corpus.

A computer identifies, within a portion of code, a code element associated with a label. The computer identifies an x-path corresponding to a value associated with the label. The computer transmits a request to translate the value. The computer receives a translated version of the value associated with the label. The computer utilizes the identified x-path to locate the value associated with the label within the portion of code. The computer updates the portion of code by replacing the value associated with the label with the translated version of the value.

A mechanism is provided in a data processing system for identifying nonsense passages. The mechanism annotates an input passage with linguistic features to form an annotated passage. The mechanism counts a number of instances of each type of linguistic feature in the annotated passage to form a set of feature counts. The mechanism determines a value for a metric based on the set of feature counts and compares the value for the metric to a predetermined model threshold. The mechanism identifies whether the input passage is a nonsense passage based on a result of the comparison.

Systems and methods of the present invention provide for one or more server computers communicatively coupled to a network and configured to: create a data table of characters, where each character in the data table is assigned a false Boolean value; for each character found in each domain name in a DNS file, update the Boolean value to true; receive a domain search request comprising a token and a TLD; generate candidate domain names using the token and the TLD; query the database to determine if any character in the domain name has the false Boolean value in the data table; and if so, remove the domain name from the candidate domain names.

Systems and methods of the present invention provide for one or more server computers communicatively coupled to a network and configured to: monitor a character stream; identify characters comprising a domain name request; identify a token in a language character map comprising the characters and associated with a language; generate, using a software translation engine, a translation of the first token into a second language; generate candidate domain names comprising: a domain name comprising the token; and a second domain name comprising the second token; modify, in real time, a user interface control to display the list of candidate domain names.

Systems and methods of the present invention provide for one or more server computers communicatively coupled to a network and configured to: receive a domain name request comprising a token and a TLD; identify a language of the token in a language map; generate candidate domain names in the language using the token and TLD; if at least of the candidate domain names comprising the TLD cannot be registered: generate, using a translation software engine, a translation of the first token into a second language; generate an alternative domain name comprising the second token and the TLD; and transmit the alternative domain name to the client computer.

A user views a video for learning a target language. The video is displayed with a caption that the user may interact with to select a phrase of interest to the user. A translation of the phrase is determined and a definition retrieved for the phrase. The translation is provided in the user's native language, and the definition may be provided in the target language. In addition, occurrences of the phrase may be identified in the remainder of the video, and a marker indicated in a timeline of the video to indicate when in the video the phrase appears, permitting the user to easily view additional contexts of the selected phrase. The user may also hide and display various interface elements to reduce reliance on the translation provided by the language learning system.

A method, system and computer-usable medium are disclosed for using a context dependency graph to automate the generation of an incorrect answer to a question suitable for a multiple choice exam. A reference corpus is used to generate a concept dependency graph that contains reference keywords and concepts associated with the subject domain of an input corpus. Relationships between the reference keywords and concepts within the concept dependency graph are identified. Once identified, they are used to process a set of input keywords and concepts extracted from the input corpus, and the reference keywords and concepts, to generate a set of distractor words. The resulting set of distractor words is then processed with a set of QA pairs associated with the input corpus to generate a set of multiple choice question-answers that include various distractor answers.