G06F40/00

Combining and displaying multiple document areas

A method includes storing, in response to marking by a user of an area of a displayed document, information on the marked area; displaying an icon representing the marked area; conducting the storing operation and the displaying operation for a different area; and creating, in response to an operation by the user for arranging two or more icons to be in contact with each other, a joined icon by joining the icons together; and combining marked areas represented by the two or more respective icons, according to a state of contact. A corresponding computer program product and computer system are also disclosed herein.

Signal analysis in a conversational scheduling assistant computing system

A software agent, that is used to assist in providing a service, receives communications from a set of users that are attempting to use the software agent. The communications include communications that are interacting with the software agent, and communications that are not interacting with the software agent. The software agent performs natural language processing on all communications to identify such things as user sentiment, user concerns or other items in the content of the messages, and also to identify actions taken by the users in order to obtain a measure of user satisfaction with the software agent. One or more action signals are then generated based upon the identified user satisfaction with the software agent.

Method and system for exploring similarities

A method and computer readable medium for exploring similar users and items of a media service includes generating a user interface. The user interface displays a user selectable indicia representing a similar member function for allowing a user to search a media service for at least one other user. The one other user has a degree of similarity with respect to the searching user. Another method includes facilitating the search of such a similar user within a media service.

Visual parsing for annotation extraction

Embodiments of the disclosure extract annotations from web pages. The annotations are combined with search results and/or advertisements to allow the user to better understand the content of the search result or advertisement landing web page. A visual snapshot of the web page is taken. Visual processing extracts information from the visual representation. The HTML, for the web page is also analyzed and various pieces of information extracted. The information from the visual processing is combined with the information extracted from the HTML. The combined information is evaluated and information for the annotations are selected. The annotations are then combined with the search results and/or advertisements.

Systems and methods for using machine learning and rules-based algorithms to create a patent specification based on human-provided patent claims such that the patent specification is created without human intervention
11651160 · 2023-05-16 · ·

Systems and methods for using machine learning and rules-based algorithms to create a patent specification based on human-provided patent claims such that the patent specification is created without human intervention are disclosed. Exemplary implementations may: obtain a claim set; obtain a first data structure representing the claim set; obtain a second data structure; obtain a third data structure; and determine one or more sections of the patent specification based on the first data structure, the second data structure, and the third data structure.

CONTENT GENERATION FRAMEWORK

Techniques for performing outputting additional content associated with but nonresponsive to an input command are described. A system receives input data from a device. The system determines an intent representing the input data and receives first output data responsive to the input data. The system determines, based on context data, that additional content associated with the first output data but nonresponsive to the input data should be output. The system receives second output data associated with but nonresponsive to the input data thereafter. The system then presents first content corresponding to the first output data and second content corresponding to the second output data.

CONTENT GENERATION FRAMEWORK

Techniques for performing outputting additional content associated with but nonresponsive to an input command are described. A system receives input data from a device. The system determines an intent representing the input data and receives first output data responsive to the input data. The system determines, based on context data, that additional content associated with the first output data but nonresponsive to the input data should be output. The system receives second output data associated with but nonresponsive to the input data thereafter. The system then presents first content corresponding to the first output data and second content corresponding to the second output data.

Systems and methods enabling online one-shot learning and generalization by intelligent systems of task-relevant features and transfer to a cohort of intelligent systems

An intelligent system, such as an autonomous robot agent, includes systems and methods to learn various aspects about a task in response to instructions received from a human instructor, to apply the instructed knowledge immediately during task performance following the instruction, and to instruct other intelligent systems about the knowledge for performing the task. The learning is accomplished free of training the intelligent system. The instructions from the human instructor may be provided in a natural language format and may include deictic references. The instructions may be received while the intelligent system is online, and may be provided to the intelligent system in one shot, e.g., in a single encounter or transaction with the human instructor.

Systems and methods enabling online one-shot learning and generalization by intelligent systems of task-relevant features and transfer to a cohort of intelligent systems

An intelligent system, such as an autonomous robot agent, includes systems and methods to learn various aspects about a task in response to instructions received from a human instructor, to apply the instructed knowledge immediately during task performance following the instruction, and to instruct other intelligent systems about the knowledge for performing the task. The learning is accomplished free of training the intelligent system. The instructions from the human instructor may be provided in a natural language format and may include deictic references. The instructions may be received while the intelligent system is online, and may be provided to the intelligent system in one shot, e.g., in a single encounter or transaction with the human instructor.

Text-based discourse analysis and management

Systems and methods of the invention determine evasiveness of postings and manage chat sessions accordingly. In embodiments, a method includes accessing a real-time text-based discourse session comprised of multiple text-based posts published by participants, the posts including a question from an author and responses from at least one respondent; determining relationships between words in the text-based discourse session utilizing corpus linguistics analysis; determining a frequency of the responses of the at least one respondent over time; determining an evasiveness score for each of the responses based on natural language processing of the responses, wherein each of the evasiveness scores indicate a level of relevance of a response with respect to the question; determining rankings for each of the responses based on the determined relationships of words, the frequency of the responses, and the evasiveness scores; and determining a display order for the responses based on the rankings of the responses.