Patents by Inventor Anandhavelu Natarajan

Anandhavelu Natarajan has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 10346861
    Abstract: Embodiments of the present invention relate to providing business customers with predictive capabilities, such as identifying valuable customers or estimating the likelihood that a product will be purchased. An adaptive sampling scheme is utilized, which helps generate sample data points from large scale data that is imbalanced (for example, digital website traffic with hundreds of millions of visitors but only a small portion of them are of interest). In embodiments, a stream of sample data points is received. Positive samples are added to a positive list until the desired number of positives is reached and negative samples are added to a negative list until the desired number of negative samples is reached. The positive list and the negative list can then be combined, shuffled, and fed into a prediction model.
    Type: Grant
    Filed: November 5, 2015
    Date of Patent: July 9, 2019
    Assignee: ADOBE INC.
    Inventors: Wei Zhang, Said Kobeissi, Anandhavelu Natarajan, Shiv Kumar Saini, Ritwik Sinha, Scott Allen Tomko
  • Publication number: 20190155913
    Abstract: Systems and techniques for searching within a document include receiving a query by way of a user interface of an application, and in conjunction with identification of the at least one document. A feature value characterizing a relevance of each grammatical unit of the document to the query may be extracted. The grammatical units may be ranked, based on each feature value of each grammatical unit. At least one selected grammatical unit of the plurality of grammatical units may then be displayed, based on the ranking.
    Type: Application
    Filed: November 17, 2017
    Publication date: May 23, 2019
    Inventors: Dhruv Singal, Ravi Teja Ailavarapu Venkata, Tirth Patel, Arghya Mukherjee, Anandhavelu Natarajan
  • Publication number: 20190147034
    Abstract: Embodiments of the present invention provide systems, methods, and computer storage media directed to facilitating predicting style breaches within content. In one embodiment, target content for which style breach prediction is desired is obtained. Style features associated with the target content are identified. Such style features and a style breach prediction model are used to predict a style breach within the target content, the style breach indicating a change of style used within the target content (e.g., a single document).
    Type: Application
    Filed: November 14, 2017
    Publication date: May 16, 2019
    Inventors: Pranav Ravindra Maneriker, Anandhavelu Natarajan, Vivek Gupta, Basava Raj K
  • Patent number: 10185987
    Abstract: In embodiments of identifying the end of an on-line cart session, an analytics application captures user click inputs on pages of a Web site, where the user click inputs include adding one or more items for purchase to an on-line cart associated with the Web site. The analytics application then utilizes a predictive model, as well as user and session features of the on-line cart session, to predict whether a previous user click input is the last user click input associated with the on-line cart session, indicating an end of the session. A notification can then be provided that the on-line cart session has ended based on the prediction of the last user click input associated with the on-line cart session. The analytics application or the marketer can then retarget a user associated with the on-line cart session, such as with a message pertaining to the on-line cart session.
    Type: Grant
    Filed: July 24, 2015
    Date of Patent: January 22, 2019
    Assignee: Adobe Inc.
    Inventors: Harsh Jhamtani, Shriram V. S. Revankar, Moumita Sinha, Balaji Vasan Srinivasan, Anandhavelu Natarajan
  • Publication number: 20180276725
    Abstract: Embodiments are disclosed for bundling and arranging online content fragments for presentation based on content-specific metrics and inter-content constraints. For example, a content management application accesses candidate content fragments, a content-specific metric, and an inter-content constraint. The content management application computes minimum and maximum contribution values for the candidate content fragments. The content management application selects, based on the computed minimum and maximum contribution values, a subset of the candidate content fragments. The content management application applies, subject to the inter-content constraint, a bundle-selection function to the selected candidate content fragments and thereby identifies a bundle of online content fragments. The content management application outputs the identified bundle of online content fragments for presentation via an online service.
    Type: Application
    Filed: August 28, 2017
    Publication date: September 27, 2018
    Inventors: Balaji Vasan Srinivasan, Shiv Kumar Saini, Kundan Krishna, Anandhavelu Natarajan, Tanya Goyal, Pranav Ravindra Maneriker, Cedric Huesler
  • Publication number: 20180211265
    Abstract: Embodiments of the present invention provide systems, methods, and computer storage media directed to facilitating predicting brand personality. In one embodiment, target content for which brand personality prediction is desired is obtained. Content features associated with the target content are identified. Such content features and a brand personality prediction model are used to predict a brand personality of the target content, the brand personality indicating personality of a brand associated with the target content.
    Type: Application
    Filed: January 23, 2017
    Publication date: July 26, 2018
    Inventors: Anandhavelu Natarajan, Niyati Himanshu Chhaya, R Sundararajan, Pradyot Prakash, Adarsh Kumar, Niloy Ganguly
  • Publication number: 20180075128
    Abstract: Identifying key terms related to an entity is described. An indication is received of the entity for which the key terms are to be identified. Content posted online about the entity and content about trending topics is collected. Since the trending topic content is collected for being trending, it is initially processed to identify items of trending topic content that are relevant to the entity. Predefined types of terms are extracted from both the posted content about the entity and the trending topic content relevant to the entity. An importance to the entity is determined for the terms extracted from the posted content about the entity and the terms extracted from the trending topic content relevant to the entity using predictive models. The key terms are identified based on importance scores computed for the extracted terms and a relevance of the extracted terms to the entity.
    Type: Application
    Filed: September 13, 2016
    Publication date: March 15, 2018
    Applicant: Adobe Systems Incorporated
    Inventors: Balaji Vasan Srinivasan, Anandhavelu Natarajan
  • Patent number: 9852239
    Abstract: A method and apparatus for prediction of community reaction to a post for an online social community is disclosed. The method comprises receiving a proposed post as input to a generated prediction model prior to the proposed post being posted to an online social community; predicting a community reaction to the proposed post using the prediction model; and displaying the predication, wherein the prediction comprises a sentiment score and at least one of a number of responses, a number of responders to the post, a longevity of the post, or a half-life of the post.
    Type: Grant
    Filed: September 24, 2012
    Date of Patent: December 26, 2017
    Assignee: ADOBE SYSTEMS INCORPORATED
    Inventors: Anandhavelu Natarajan, Balaji Vasan Srinivasan, Vineet Gupta, Anand Ganesan, Anuj Jain, Shriram Revankar, Japnik Singh, Bharat Polineni
  • Publication number: 20170132516
    Abstract: Embodiments of the present invention relate to providing business customers with predictive capabilities, such as identifying valuable customers or estimating the likelihood that a product will be purchased. An adaptive sampling scheme is utilized, which helps generate sample data points from large scale data that is imbalanced (for example, digital website traffic with hundreds of millions of visitors but only a small portion of them are of interest). In embodiments, a stream of sample data points is received. Positive samples are added to a positive list until the desired number of positives is reached and negative samples are added to a negative list until the desired number of negative samples is reached. The positive list and the negative list can then be combined, shuffled, and fed into a prediction model.
    Type: Application
    Filed: November 5, 2015
    Publication date: May 11, 2017
    Inventors: WEI ZHANG, SAID KOBEISSI, ANANDHAVELU NATARAJAN, SHIV KUMAR SAINI, RITWIK SINHA, SCOTT ALLEN TOMKO
  • Publication number: 20170024807
    Abstract: In embodiments of identifying the end of an on-line cart session, an analytics application captures user click inputs on pages of a Web site, where the user click inputs include adding one or more items for purchase to an on-line cart associated with the Web site. The analytics application then utilizes a predictive model, as well as user and session features of the on-line cart session, to predict whether a previous user click input is the last user click input associated with the on-line cart session, indicating an end of the session. A notification can then be provided that the on-line cart session has ended based on the prediction of the last user click input associated with the on-line cart session. The analytics application or the marketer can then retarget a user associated with the on-line cart session, such as with a message pertaining to the on-line cart session.
    Type: Application
    Filed: July 24, 2015
    Publication date: January 26, 2017
    Inventors: Harsh Jhamtani, Shriram V.S. Revankar, Moumita Sinha, Balaji Vasan Srinivasan, Anandhavelu Natarajan
  • Patent number: 9256826
    Abstract: This document describes techniques for predicting reactions to short-text posts. In one or more implementations, a prediction model for short-text posts is generated from previous posts to a social network and responses to the posts by the social network community. Subsequently, the prediction model can be used to predict the social network community's reaction to a proposed post prior to the proposed post being posted to the social network.
    Type: Grant
    Filed: August 14, 2013
    Date of Patent: February 9, 2016
    Assignee: Adobe Systems Incorporated
    Inventors: Balaji Vasan Srinivasan, Anandhavelu Natarajan, Ritwik Sinha, Vineet Gupta, Shriram V. Revankar, Balaraman Ravindran
  • Publication number: 20150170294
    Abstract: A computer implemented method and apparatus for scheduling multiple social media posts to maximize engagement and on-site activity. The method comprises accessing a plurality of posts and scheduling information for the plurality of posts, wherein the scheduling information comprises a time period during which the plurality of posts is to be scheduled for posting on an online social media site; predicting a response to each post at a plurality of times that fall within the time period; and scheduling, based on the predicted responses to each post, a time to post each post of the plurality of posts, wherein scheduling maximizes the predicted response to each post.
    Type: Application
    Filed: December 17, 2013
    Publication date: June 18, 2015
    Applicant: ADOBE SYSTEMS INCORPORATED
    Inventors: Pawan Goyal, Mohit Garg, Ankur Jain, Vivek Kumar, Anandhavelu Natarajan
  • Publication number: 20150052087
    Abstract: This document describes techniques for predicting reactions to short-text posts. In one or more implementations, a prediction model for short-text posts is generated from previous posts to a social network and responses to the posts by the social network community. Subsequently, the prediction model can be used to predict the social network community's reaction to a proposed post prior to the proposed post being posted to the social network.
    Type: Application
    Filed: August 14, 2013
    Publication date: February 19, 2015
    Applicant: Adobe Systems Incorporated
    Inventors: Balaji Vasan Srinivasan, Anandhavelu Natarajan, Ritwik Sinha, Vineet Gupta, Shriram V. Revankar, Balaraman Ravindran
  • Publication number: 20140088944
    Abstract: A method and apparatus for prediction of community reaction to a post for an online social community is disclosed. The method comprises receiving a proposed post as input to a generated prediction model prior to the proposed post being posted to an online social community; predicting a community reaction to the proposed post using the prediction model; and displaying the predication, wherein the prediction comprises a sentiment score and at least one of a number of responses, a number of responders to the post, a longevity of the post, or a half-life of the post.
    Type: Application
    Filed: September 24, 2012
    Publication date: March 27, 2014
    Applicant: Adobe Systems Inc.
    Inventors: Anandhavelu Natarajan, Balaji Vasan Srinivasan, Vineet Gupta, Anand Ganesan, Anuj Jain, Shriram Revankar, Japnik Singh, Bharat Polineni