Google Inc.

International Business Machines Corporation

Yahoo! Inc.

Kishore A Papineni

Henry Allan Rowley

Sanjiv Kumar

Xiaohang Wang

Alessandro Bissacco

Radu Florian

Abraham P Ittycheriah

Jeffrey Scott Sorensen

Luiz Do Amaral De Franca Pereira Filho

Salim Estephan Roukos

Robert T Ward

John C Langford

Jose Jeronimo Moreira Rodrigues

Randolph Preston McAfee

Andrea Zvinakis

Brian Kravitz

Shruti Gupta

Yaser Al-Onaizan

Richard Zens

Shyam Parikkal Krishnamurthy

Boris Dadachev

Christopher Welty

Jayakumar Hoskere Gireesha

Anmol Gulati

Systems and methods are described to suggest new content to a writer. An intelligent tool is initiated to obtain content of a document that is being written by an author. The intelligent tool then determines a topic of the content of the document, and identifies one or more predictive topics related to the determined topic. The one or more predictive topics are different from the topic. The intelligent tool then performs a content search based on the topic and the one or more predictive topics, and provides results from the content search to the author.

Systems and methods for suggesting content to a writer based on contents of a document

Example aspects of the present disclosure are directed to systems and methods that employ a machine-learned opinion classification model to classify portions (e.g., sentences, phrases, paragraphs, etc.) of documents (e.g., news articles, web pages, etc.) as being opinions or not opinions. Further, in some implementations, portions classified as opinions can be considered for inclusion in an informational display. For example, document portions can be ranked according to importance and selected for inclusion in an informational display based on their ranking. Additionally or alternatively, for systems which access and consider multiple documents, the portions of a document that are classified as opinion can be compared to similarly-classified portions of other documents to perform document clustering, to ensure diversity within a presentation, and/or other tasks.

Machine learning to identify opinions in documents

Systems and methods are described to notify an author that suggested content is available. An author-assistance tool is instantiated with a document processor to perform research to suggest content for a document being edited at the document processor. A user interaction relating to a document is received via the document processor, and the author-assistance tool generates suggested content for the document when the author has intent for content suggestion or the document has a document type that is on a list of document types for which a content suggestion should be made. The author-assistance tool then determines that the suggested content meets a pre-determined quality threshold, and generates, via the user interface of the document processor, a notification to the author that the suggested content is available.

Systems and methods for notifying an author of contextual suggested content

Embodiments herein provide computer-implemented techniques for allowing a user computing device to extract financial card information using optical character recognition ('OCR'). Extracting financial card information may be improved by applying various classifiers and other transformations to the image data. For example, applying a linear classifier to the image to determine digit locations before applying the OCR algorithm allows the user computing device to use less processing capacity to extract accurate card data. The OCR application may train a classifier to use the wear patterns of a card to improve OCR algorithm performance. The OCR application may apply a linear classifier and then a nonlinear classifier to improve the performance and the accuracy of the OCR algorithm. The OCR application uses the known digit patterns used by typical credit and debit cards to improve the accuracy of the OCR algorithm.

Extracting card data with wear patterns

A content item is requested by a user via the user's computing device. In response, data, such as a set of facts, related to the requested content item is identified and served with the requested content item for presentation with the content item at the user's computer device. The related data can comprise facts related to the content item, and the related data can be presented as a graphic, such as part of a multi-dimensional graph, in connection with the presentation of the content. The related data can be retrieved from a facts database using search criteria formed using tags obtained for the requested content item.

System and method for automatic presentation of content-related data with content presentation

Embodiments are directed towards employing an admission controller (AC) network device to coordinate voluntary requests by traffic source devices (TSDs) to transmit traffic over a network. The TSDs submit voluntary requests to transmit network traffic during an allocated time frame to the AC. The AC monitors historical network traffic data and, based on various allocation policies, provides permission to at least some of the TSDs in the form of a nonexclusive lease of bandwidth with a rate cap for an allocated time frame. The TSDs receiving the lease voluntarily agree to transmit traffic not exceeding the rate cap for the time frame of the lease. TSDs that receive a zero rate cap voluntarily agree not to transmit. However, urgent network traffic bypasses the AC. The allocation policies used to determine the rate cap and number of permitted senders include a reactive approach, a predictive approach, and a predictive-reactive approach.

Voluntary admission control for traffic yield management

A method, computer program product and system are provided. The method includes the steps of: providing output text and a confidence value and displaying the output text. The output text includes text in a second language produced from machine translation performed on input text in a first language. The confidence value corresponds to an indication of reliability of the output text. The display of the output text includes a display attribute corresponding to the confidence value of the output text.

Visualization method for machine translation

A system for conversant interaction includes a recognizer for receiving and processing input information and outputting a recognized representation of the input information. A dialog manager is coupled to the recognizer for receiving the recognized representation of the input information, the dialog manager having task-oriented forms for associating user input information therewith, the dialog manager being capable of selecting an applicable form from the task-oriented forms responsive to the input information by scoring the forms relative to each other. A synthesizer is employed for converting a response generated by the dialog manager to output the response. A program storage device and method are also provided.

Natural language task-oriented dialog manager and method

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Yonkers, NY, United States of America

Kishore A Papineni