Patents by Inventor Suleyman Cetintas

Suleyman Cetintas 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).

  • Publication number: 20170032424
    Abstract: The technologies described herein serve contextually relevant advertisements under a guaranteed advertisement campaign. A publisher retrieves a guaranteed advertisement campaign related to a webpage available for serving an advertisement, and identifies a set of advertisements relating to the guaranteed advertisement campaign. Advertisement selecting circuitry of the publisher determines whether an advertisement that is contextually relevant to content published at the webpage is present in the set of advertisements. If there is no contextually relevant advertisement in the set of advertisements, the advertisement selecting circuitry selects an alternative advertisement from the set of advertisements that minimizes an under-delivery risk related to the guaranteed advertisement campaign. If there is a contextually relevant advertisement in the set of advertisements, the advertisement selecting circuitry selects the contextually relevant advertisement.
    Type: Application
    Filed: July 31, 2015
    Publication date: February 2, 2017
    Applicant: Yahoo! Inc.
    Inventors: Suleyman Cetintas, Srinath Ravindran, Mohammad Saberian, Sandeep Soni, Kuang-chih Lee, Hong Yao, Jian Yang, Pradhan Pattanayak
  • Publication number: 20160299992
    Abstract: Users may consume and/or share information through various types of content items. For example, user may post a family photo through a social network, create a running blog through a microblogging service, etc. Because users may be overwhelmed by the amount of available content items, it may be advantageous to recommend content items, such as blogs to follow, to users. Accordingly, inductive matrix completion is used to evaluate user interactions with content items (e.g., a user following a blog), content item features (e.g., text and/or images of a blog is evaluated to identify a topic of the blog), and/or user features (e.g., a user liking or reblogging a blog, user demographics, user interests, etc.) to determine whether to recommend a content item to a user. Additionally, graph proximity is used to recommend content items based upon weights of edges connecting user nodes to content item nodes within a directed graph.
    Type: Application
    Filed: April 9, 2015
    Publication date: October 13, 2016
    Inventors: Suleyman Cetintas, Kuang-chih Lee
  • Publication number: 20160180162
    Abstract: Briefly, embodiments of methods and/or systems of generating preference indices for contiguous portions of digital images are disclosed. For one embodiment, as an example, parameters of a neural network may be developed to generate object labels for digital images. The developed parameters may be transferred to a neural network utilized to generate signal sample value levels corresponding to preference indices for contiguous portions of digital images.
    Type: Application
    Filed: December 22, 2014
    Publication date: June 23, 2016
    Inventors: Suleyman Cetintas, Kuang-chih Lee, Jia Li
  • Publication number: 20160180374
    Abstract: Described herein are solutions for improving management of viewable impression based display advertising systems. For example, described herein are solutions for improving management of viewable impression based display advertising systems amongst various online marketing channels, such as search engine and guaranteed display advertising (GDA) marketing channels. The solutions can include use of a legacy GDA system and a score (e.g., a ratio) to bridge viewable impression based control and pricing and regular impression based control and pricing.
    Type: Application
    Filed: December 17, 2014
    Publication date: June 23, 2016
    Applicant: YAHOO! INC.
    Inventors: Suleyman Cetintas, Konstantin Shmakov, Isay Shnayder, Lalit Pandey, Ning Cao