International Business Machines Corporation

Snap Inc.

Airbnb, Inc.

Liam S Harpur

Jonathan D Dunne

Al Chakra

John Rice

Lin Sun

Patrick Joseph O'Sullivan

Jeremy R Fox

Paul R Bastide

Kelley Anders

Judith Helen Bank

Ruthie D Lyle

Matthew E Broomhall

Asima Silva

Robert E Loredo

Trudy L Hewitt

Fred Raguillat

Carol Sue Zimmet

Sumit Patel

Lisa M W Bradley

Colm Farrell

Mark Y Kelly

Aaron J Quirk

Erik H Katzen

Shikhar Kwatra

Barry Edward Willner

Simon P O'Doherty

Michelle M Purcell

James Patrick Galvin, Jr

Gary Denner

Edith H Stern

Robert Huntington Grant

Joseph M Jaquinta

Mette F M Hammer

Pauli P O Nurmenkari

Lisa M Bradley

Amy D Travis

John Kennedy

Sean K Dunne

Sarbajit Kumar Rakshit

Zachary A Silverstein

Hernan A Cunico

Hema Srikanth

David M Curran

Daniel Terlizzi

Peter M McGrath

Rob A Gearhart

Martin A Flint

John C Rice

Gregory J Boss

Itzhack Goldberg

Mark Patrick Delaney

Hitham Ahmed Assem Aly Salama

Soumitra G Limaye

Anuradha D Chitta

Ranjit S Rai

Yuk Lung Chan

Eric Woods

Adam Lee Griffin

Daniel John McCloskey

Matthew Francis Rutkowski

Chris Kau

Cynthia E Barber-Mingo

Arno Denne

Francesco Mariani

Paula Prendergast

Christopher J Hardee

Sushain Pandit

Jonathan Frederick Brunn

David Yu Chang

Stanley Kieran Jerrard-Dunne

Messaoud Benantar

Vishwanath Venkataramappa

Christian Benjamin Kau

Brian O'Donovan

Andrew T Penrose

Bo Jiang

Paulito Pedregosa Palmes

Niall Brady

Nithinkrishna Shenoy

Brett Ward

Eduardo A Patrocinio

Ethan A Geyer

Naama Tepper

Vaishnavi Nori

Craig M Trim

Maharaj Mukherjee

Jonathan Lenchner

John David Wilson

Qi Cheng Li

Cesar Augusto Rodriguez Bravo

David Bruce Lection

Mark B Stevens

Sean Callanan

David G Robinson

Jason Flood

Mahesh Shivram Paradkar

Lisa Marie Wood Bradley

Daniel C Gurney

Rogelio Vazquez-Rivera

Vivek Jain

A method for prohibiting email content propagation that receives, at a server, an email message. At the server, at least one email address associated with the email message which is designated not to receive a content of the email message is identified. At the server, the email message is modified by selectively removing a content of the email message to be conveyed to the at least one email address. The server conveys the modified email message to the at least one email address. The server conveys the email message to one or more recipient email addresses except the at least one email address. Consequently, the server has sent a submitted message to multiple email addresses, while modifying the content sent to a subset of the addresses that received the email message.

Prohibited content propagation using a social network data structure

A system for generating of posts, the system including: a server; and a network connection for the server; the server to: maintain a database of users and corresponding user behavior when generating a post on a specific topic; match a first user generating a current post and a topic of the current post to user behavior in the database; based on the matching user behavior from the database, identify different versions during development of the current post; and dictate distribution of different versions of the post based on the matching user behavior from the database.

System for social versioning

An embodiment of a summarization application divides collected conversation data into media and text components. The application implements respective machine learning mechanisms to enhance modeling operations of the text and media components to identify key elements from the conversation. The application generates a headline banner from a group of key elements based on an analysis involving first predetermined criteria. The application also combines additional key elements to the group of key elements to form a second group of key elements. The application generates a summary from the second group of key elements based on a second analysis involving second predetermined criteria. The application presents, via a display, the headline banner according to a first output of the first key element analysis and the summary according to a second output of the second key element analysis.

Summarizing multi-modal conversations in a multi-user messaging application

In an approach for conversational interchange optimization, a processor monitors conversations in a communication system. A processor generates a list of topics in the conversations. A processor determines a flow for each topic based on length of time, number of participants, and sentiment associated to each topic. The flow is the progress of interactions and shifts for each topic. A processor builds a statistical model for each topic based on the flow to predict success or failure of a topic progression for an incoming conversation. A processor updates the topic progression for the incoming conversation based on the predicted success or failure.

Conversational interchange optimization

The method, computer program product and computer system may include computing device which may collect application data from an application and archive the application data into a datastore. The computing device may generate a network graph based on the archived application data. The computing device may detect a new message, containing content on one or more topics, posted in the application by an author. The computing device may determine familiarity of an anticipated user with the content of the new message and associate the new message with a message history in the application based on the anticipated user. The computing device may generate a message content summary of the new message based on the message history and present message content summary to the anticipated user.

Content analysis and context summary generation

A second action is identified by the edged device. The second action is associated with a second networked device of the plurality of networked devices in the environment. The second networked device is unrelated to the first networked device. A relationship is detected between the first networked device and the second networked device by the edge device. A network device bubble is generated by the edge device. The network device bubble is based on the relationship that is detected.

Smart home bubble creation

Techniques for patterned and correlated electrical activity include receiving user data from a device of a user and anonymized data from other devices of other users, the user data and the anonymized data being received based on the device and the other devices having been co-located. The user data is compared to the anonymized data according to an activity. It is determined that an event occurred based on one or more deviations of the user data from the anonymized data according to the activity, the event being related to a health of the user.

Patterned and correlated electrical activity

Methods, computer program products, and systems are presented. The methods include, for instance: inputs of emotion time series data of a user and environmental factor data from one or more data collection device for a user assistance service. A baseline emotion time series is generated and an environmental factor that is likely to have affected changes in state of emotion on a subject is identified by regression analysis. An emotion time series model for the identified environmental factor is produced and prediction of a path to attain a target state of emotion at a certain time in the future is made. Recommendation to achieve the target state of emotion is produced based on the predicted path.

State of emotion time series

A method, apparatus and computer program product for modifying a user interface in a web browsing session is described. During a learning session with a first user, a user model is created. The user model includes associating user movement of the first user with a set of user focus types. During the web browsing session with the first user, the system determines that a first user focus of the set of user focus types in the user model is appropriate to modify a web application user interface to present a priority user interface element in the user interface. The web application user interface is modified according to the first user focus.

Modifying user interface layout based on user focus

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.

Text-based discourse analysis and management

A method comprises analyzing a first portion of content displayed on a device of a user to identify a topic of the first portion of the content; selecting a mitigation action based on the identified topic and a profile of the user, wherein the mitigation action is configured to decrease interest of the user in consuming the displayed content; and modifying the displayed content on the device of the user based on the selected mitigation action.

Interest tapering for topics

An approach is described for addressing propagation of inaccurate information in a social networking environment. An associated method may include identifying inaccurate information within the social networking environment, facilitating creation of countering content to address the inaccurate information, and disseminating the countering content. The countering content may be determined by identifying behavior of one or more users among a plurality of users within the social networking environment. Identifying the inaccurate information within the social networking environment may include receiving information provided within the social networking environment. Upon determining that the received information is factual and thus objectively verifiable, it may be determined whether the received information matches analogous information verified as accurate. Upon determining that the received information does not match the analogous information verified as accurate, the received information may be marked as inaccurate.

Addressing propagation of inaccurate information in a social networking environment

Growing community of inventors

Dublin, Ireland

Liam S Harpur