Abstract: The present disclosure provides a system for predicting the difficulty of an exam question in which a training module uses training data to create a machine learning model to predict the difficulty of a question, and the difficulty module collects inputted questions and answers from a teacher that are inputted through an education network into the machine learning model, and the difficulty of the question is displayed.

Abstract: Systems and methods are provided for proctoring online exams that collects reference samples of a student's speech and video of them looking at their computer screen. Audio and video of the student are then captured during the exam. That audio and video is segmented and compared to the reference samples in order to identify segments that potentially contain at least one of another speaker who is not the student, the student looking away from the computer screen, another face that is not the student's. The frequency and severity of flagged segments are used to indicate the overall level of suspicion to an exam proctor.

Abstract: Systems and methods are provided for custom online course based on matching content with a course syllabus by parsing a syllabus document submitted by a teacher into course segments and matches course resources with appropriate course segments. The course segments can be automatically placed into an online course structure. The appropriate course materials can then be automatically matched to each course segment. Teachers may then approve, edit, or delete course segments and their matched materials. This approval process may improve the syllabus parsing and content matching and content generation using machine-learning models, such as large language models.

Abstract: Computing system resources are controlled based on the behavioral attributes associated with users of the computing system. These behavioral attributes are monitored in real time and through a historical log, and behavioral attributes that fall outside pre-determined preferred behavioral parameters are detected. Access by the computing system user to computing system resources contained in a preferred and habitually accessed computing system resource set associated with the computing system user are adjusted in response to the detection of the behavioral attribute outside the pre-determined preferred behavioral parameters.

Abstract: Creating training data for a natural language processing system may comprise obtaining natural language input, the natural language input annotated with one or more important phrases; and generating training instances comprising a syntactic parse tree of nodes representing elements of the natural language input augmented with the annotated important phrases. In another aspect, a classifier may be trained based on the generated training instances. The classifier may be used to predict one or more potential important phrases in a query.

Abstract: Computing system resources are controlled based on the behavioral attributes associated with users of the computing system. These behavioral attributes are monitored in real time and through a historical log, and behavioral attributes that fall outside pre-determined preferred behavioral parameters are detected. Access by the computing system user to computing system resources contained in a preferred and habitually accessed computing system resource set associated with the computing system user are adjusted in response to the detection of the behavioral attribute outside the pre-determined preferred behavioral parameters.

Abstract: Computing system resources are controlled based on the behavioral attributes associated with users of the computing system. These behavioral attributes are monitored in real time and through a historical log, and behavioral attributes that fall outside pre-determined preferred behavioral parameters are detected. Access by the computing system user to computing system resources contained in a preferred and habitually accessed computing system resource set associated with the computing system user are adjusted in response to the detection of the behavioral attribute outside the pre-determined preferred behavioral parameters.

Abstract: An embodiment of the invention directed to a method is associated with data content, comprising discrete data portions including first data and second data portions separated from each other in the data content. A copy operation is implemented on data portions so that at least some of the data portions are each copied to a buffer, which include the first and second data portions. A paste operation is carried out to present each of the copied data portions as an input for an output data selection task. Prespecified criteria is used in the output data selection task to select a number of the copied data portions to be selected data for a given purpose, the selected number of copied data portions being less than data portions presented by the paste operation, and the selected copied data portions including the first and second data portions.

Abstract: Techniques for client side translation cache prediction are provided. The techniques include obtaining meta data associated with a request, applying a cache prediction model to the meta data to automatically predict one or more translations associated with the request, and storing the one or more translations in a client translation cache.

Abstract: Techniques for facilitating communication are provided. The techniques include using a machine-to-machine communication to facilitate communication between one or more human users of a communicator device and a compatible communicator device, wherein using the machine-to-machine communication to facilitate communication between one or more human users comprises initiating a machine-to-machine communication with a compatible communicator device if the device is within the geographic proximity, wherein the machine-to-machine communication incorporates one or more related items from a user profile of each device automatically extracted by the device initiating the machine-to-machine communication, and conducting the machine-to-machine communication in a manner in which the communication can be monitored by the one or more human users.

Abstract: Creating training data for a natural language processing system may comprise obtaining natural language input, the natural language input annotated with one or more important phrases; and generating training instances comprising a syntactic parse tree of nodes representing elements of the natural language input augmented with the annotated important phrases. In another aspect, a classifier may be trained based on the generated training instances. The classifier may be used to predict one or more potential important phrases in a query.

Abstract: An embodiment of the invention directed to a method is associated with data content, comprising discrete data portions including first data and second data portions separated from each other in the data content. A copy operation is implemented on data portions so that at least some of the data portions are each copied to a buffer, which include the first and second data portions. A paste operation is carried out to present each of the copied data portions as an input for an output data selection task. Prespecified criteria is used in the output data selection task to select a number of the copied data portions to be selected data for a given purpose, the selected number of copied data portions being less than data portions presented by the paste operation, and the selected copied data portions including the first and second data portions.

Abstract: Computing system resources are controlled based on the behavioral attributes associated with users of the computing system. These behavioral attributes are monitored in real time and through a historical log, and behavioral attributes that fall outside pre-determined preferred behavioral parameters are detected. Access by the computing system user to computing system resources contained in a preferred and habitually accessed computing system resource set associated with the computing system user are adjusted in response to the detection of the behavioral attribute outside the pre-determined preferred behavioral parameters.

Abstract: Computing system resources are controlled based on the behavioral attributes associated with users of the computing system. These behavioral attributes are monitored in real time and through a historical log, and behavioral attributes that fall outside pre-determined preferred behavioral parameters are detected. Access by the computing system user to computing system resources contained in a preferred and habitually accessed computing system resource set associated with the computing system user are adjusted in response to the detection of the behavioral attribute outside the pre-determined preferred behavioral parameters.

Abstract: Techniques for client side translation cache prediction are provided. The techniques include obtaining meta data associated with a request, applying a cache prediction model to the meta data to automatically predict one or more translations associated with the request, and storing the one or more translations in a client translation cache.

Abstract: A device, method, and computer program for performing language translation. An example embodiment may include a communications module configured to receive device data from a nearby device. A constraint module is configured to limit a translation domain of the language translation based on the device data. Language translation is performed within the limited translation domain.

Abstract: Techniques for facilitating communication are provided. The techniques include using a machine-to-machine communication to facilitate communication between one or more human users of a communicator device and a compatible communicator device, wherein using the machine-to-machine communication to facilitate communication between one or more human users comprises initiating a machine-to-machine communication with a compatible communicator device if the device is within the geographic proximity, wherein the machine-to-machine communication incorporates one or more related items from a user profile of each device automatically extracted by the device initiating the machine-to-machine communication, and conducting the machine-to-machine communication in a manner in which the communication can be monitored by the one or more human users.

Abstract: Systems and methods relate to generating a language model for use in, for example, a spoken dialog system or some other application. The method comprises building a class-based language model, generating at least one sequence network and replacing class labels in the class-based language model with the at least one sequence network. In this manner, placeholders or tokens associated with classes can be inserted into the models at training time and word/phone networks can be built based on meta-data information at test time. Finally, the placeholder token can be replaced with the word/phone networks at run time to improve recognition of difficult words such as proper names.