Wipro Limited

Rovi Guides, Inc.

International Business Machines Corporation

Adeia Guides Inc.

Amazon Technologies, Inc.

Groupon, Inc.

Sap Se

Lenovo (singapore) Pte. Ltd.

Bsh Hausgeräte Gmbh

Vijay A Kumar

Thomas Chittakattu Ninan

Madhusudhan Srinivasan

Rajendran Pichaimurthy

Shagun Rai

Gyanveer Singh

Urvashi Verma

Kuntal Dey

Charanjit Singh Jutla

Pradeep Kumar Dubey

Danish Contractor

Amber Roy Chowdhury

Sreekanth L Kakaraparthy

Vikram Makam Gupta

Prakash Viswanathan

Joseph Edward Bolan

Krishna Kummamuru

Vijay Krishnarao Naik

Madhusudhan Seetharam

John Arthur Pershing, Jr

Balaji Sunil Kumar

Lawrence Lee Wai

Pradeep Varma

Roger Henry Castillo

Bhupesh Bansal

William Francis Jerome

Sri Subramaniam

Ajay Raina

Sridatta Viswanath

Sameh Afif Fakhouri

Saurav Labana

Alexander Y Kalinin

Hemachandra Ramanath Bhat

Seema Nagar

Malcolm Scott Ware

Chai Wah Wu

Charles Philippe Tresser

Pankaj Rohatgi

Peter Richard Badovinatz

Josyula R Rao

Suresh Kumar

Keith Manders Campbell

Marco Martens

Pooja Aggarwal

Jonathan David Phillips

Alok Aggarwal

Brian Jeffrey Saltzman

Pierre Galin

Utkarsh Dwivedi

Michael I Shub

Santhosh Kumar Madathil

Mehmet A Elicin

Kishan Rao Ramesh Yaradi

Ankit Jain

Ankita Kalra

Atri Rudra

Ramya Kolli

Chien-Chung Huang

Yateesh Kumar Shivarudraiah

Ramkumar Gandhinathan

Ravindran Sai Anand

Suresh Kumar P

Prasanna Ganesan

Bhuvaneswari D

Krishnendu Chatterjee

Peter B Badovinatz

Kiran Pal Sagoo

Matthias Mayr

Harish Kumar Kumar

Naveen Konanoor

Mohankumar Kumaran

Praveen Prathima Shivaramaiah

Systems and methods are described herein for automatically identifying spam in social media comments based on comparison of the context or topic of the popular or trending post with the context or topic of each comment associated with the post. Content of a social media post is processed to identify a topic of the social media post. A plurality of comments associated with the social media post are accessed and the topic of each comment is compared to the topic of the social media post and, if the topics do not match, the comment is identified as spam. A notification is generated for display to an administrator of the social media platform on which the social media post resides identifying the comment as spam.

Systems and methods for automatically identifying spam in social media comments based on context

Systems and methods are disclosed herein for providing a recommendation to modify deficient a deficient content item. A plurality of content items associated with a topic is retrieved. Each of the content items includes a plurality of portions each associated with a respective sub-topic. A rating for each sub-topic of the content items is calculated, and a minimum viable subset of the sub-topics is identified based on the calculated ratings. A new content item associated with the topic is accessed. A plurality of portions of the new content item is identified and a sub-topic for each identified portion is determined. An omitted sub-topic of the minimum viable subset of the sub-topics that is not included in the sub-topics of the new content item is identified, and the system interrupts upload of the new content and recommends modifying the new content item to include a portion with the omitted sub-topic.

Systems and methods for providing recommendation to modify deficient content item

Systems and methods for curation of content, such as e-learning content or online instructional materials, according to particular criteria such as the amount of pictorial representations contained therein, the amount of verbal expression contained therein, and whether the content contains a summary. Other criteria may also be employed. Users may select any one or more of these and other criteria. Content is then sorted according to the selected criteria and presented as an ordered list of content that users can select for viewing.

Method and apparatus for curation of content

Systems and methods for enhancing virality for a content item are disclosed herein. A content item is uploaded to a content sharing platform over a communication network. Feedback on the content item is received from the content sharing platform over the communication network. Based on the feedback, a virality score for the content item is determined and a determination is made as to whether the virality score meets a virality criterion. In response to a determination that the virality score does not meet the virality criterion, a virality enhancement technique is selected from a virality enhancement database, the content item is modified by applying the virality enhancement technique to the content item, and the modified content item is uploaded to the content sharing platform over the communication network.

Automated content virality enhancement

Systems and associated methods are described for determining popularity of new content. The system analyzes a content item to identify at least a first and a second attribute associated with the content item. The system also identifies previously posted content items associated with the first and the second attributes. The system then determines levels of user activity associated with the previously posted content item corresponding to the first attribute over a first past time period and associated with the previously posted content item corresponding to the second attribute over a second past time period. The system then extrapolates a levels of user activity for a future time period based on the first past time period and on the second past time period. The system further determines an anticipated level of user activity associated with the content item for the future time period based on the extrapolated levels of user activity.

Systems and methods for adjusting storage based on determining content item popularity

Methods and systems for curating notifications from unfollowed accounts are described herein. The system tracks that a first account previously followed a second account and subsequently unfollowed the second account. The system identifies an interest of the first account and monitors the activities of the second account for activity that matches the interest. If there is a match between the interest and an activity of the second account, the system notifies the first account of the activity. These methods and systems provide the user with relevant information from unfollowed accounts.

Systems and methods to curate notifications from unsubscribed social media accounts

Systems and methods are described herein for selecting content providers based on performance scores of the respective content providers. The system monitors the performance of a content provider, where the performance is based on the quality of service for receiving a media content item from the content provider. Based on the monitored performance, the system may determine if an adequate performance is not achievable. In response to determining that an adequate performance is not achievable, the system compares the performance of the content provider to the performance of a second content provider and provides, on the user device, the media content item from the second content provider.

Systems and methods for switching content providers to maintain streaming experience

Systems and methods are described herein for generating alternate audio for a media stream. The media system receives media that is requested by the user. The media comprises a video and audio. The audio includes words spoken in a first language. The media system stores the received media in a buffer as it is received. The media system separates the audio from the buffered media and determines an emotional state expressed by spoken words of the first language. The media system translates the words spoken in the first language into words spoken in a second language. Using the translated words of the second language, the media system synthesizes speech having the emotional state previously determined. The media system then retrieves the video of the received media from the buffer and synchronizes the synthesized speech with the video to generate the media content in a second language.

Translating a media asset with vocal characteristics of a speaker

The system generates a validation tool in response to receiving an indication to initiate validation. The system identifies at least one media content item based on a user profile, and generates at least one question based on the at least one media content item. The at least one media content item may include an image, a video, text, or a combination thereof. The system determines at least one answer corresponding to the at least one question. The question and answer may be determined based on a question template. For example, the template may be selected based on attribute types or values of the at least one media content item. The system generates the at least one question for output on an output device. Upon receiving input indicative to an answer, the system compares the inputted answer to the determined answer to determine whether to validate the user.

Systems and methods for providing user validation

Systems and methods are disclosed herein for applying behavioral-based parental controls for media assets. The disclosed techniques herein discuss determining a media asset viewed by a user and character actions of a character within the media asset. Behavioral user data is received which includes a user action. A determination is made whether the user action matches one of the character actions. If a match is found, a parental control restriction setting for the media asset is applied and this parental control restriction is stored in memory.

Systems and methods for applying behavioral-based parental controls for media assets

Digital teaching content ordering includes receiving, by a data processing system, digital teaching content and any corresponding annotations and content heuristic(s) from a teacher or other presenter, the digital teaching content including text and/or image(s). The data processing system monitors student gaze of the digital teaching content during a class and can cognitively skip some of the digital teaching content during the class based on the monitored student gaze and content heuristic(s). The system can also cognitively modify the digital teaching content outside of class based, in part, on the monitoring and the content heuristic(s). A hypergraph of the digital teaching content may also be received, the cognitively skipping being further based on the hypergraph, and the cognitively modifying being further based on a heat map built using the hypergraph and the student gaze.

Dynamicaly updating digital visual content via aggregated feedback

Growing community of inventors

Bengaluru, India

Vijay A Kumar