Oracle International Corporation

Blue Kai, Inc.

Yahoo! Inc.

John Patrick Connelly

David Abraham Wiener

Vernon W Hui

Michael David Bigby

James Kong Hsu

Kendra Mariko Chen

Stephen John Papa

Edward L Wallace

Lucian Vlad Lita

Matthew Perry Abrams

Charles Yang

Sherene Wael Hilal

Ben Hekster

Mayank Ashwin Dedhia

Guy Lewis Steele, Jr

Andrew Brownsword

David Lawrence Rager

Anping Wang

David Scott Gardner

Venkat Panchapakesan

Jeevan Gheevarghese Joseph

Ron Nordan

Seth Godin

Vernon Wah-Non Hui

Eric Boyd

Robert Otto Barnes, Ii

Hyunjung Lee

Hong Bao

Sanjeev Khodaskar

Thomas Churchill

Henry Hyunsuk Sohn

David Conway

Rahul Dilip Jagad

Disclosed are techniques for processing user profiles using data structures that are specialized for processing by a GPU. More particularly, the disclosed techniques relate to systems and methods for evaluating characteristics of user profiles to determine whether to offload certain user profiles to the GPU for processing or to process the user profiles locally by one or more central processing units (CPUs). Processing user profiles may include comparing the interest tags included in the user profiles with logic trees, for example, logic trees representing marketing campaigns, to identify user profiles that match the campaigns.

Enhanced processing of user profiles using data structures specialized for graphical processing units (GPUs)

A server receives incoming data records comprising an ID value and respective user attributes corresponding to a user activity that originates at a user device. Characteristics of the activity and/or characteristics of the user device are considered in order to assign a probabilistic confidence value, which is in turn used to generate links from an incoming data record to other previously-received data records, and in so doing, generates a probabilistic link between one set of user attributes from the incoming data record and another set of user attributes from previously-received data records. A messaging campaign specification that describes target user attributes is used to identify a matching set of target audience member records. The determination of a match or not is based on the probabilistic confidence value and a threshold can be varied to extend audience reach. The identified set of target audience member records are transmitted over a network.

Extending audience reach in messaging campaigns using probabilistic ID linking

Techniques are provided to quickly process stored objects to generate an accurate estimate of the number of live objects that will be responsive to a client's filtering request defined at least in part based on a filtering parameter. Stored objects generated from user interactions with webpages are modified to simulate live objects and processed by a live object-intake simulator. The simulated results are then filtered using the filtering parameter to form a subset of matching objects. An estimate of the number of live objects produced by the filtering parameter is generated using at least the count of the objects in the subset. A confidence metric of the estimate is computed, in some cases using a statistical model. Under certain conditions, the estimate is delivered, the confidence metric is delivered, and/or live object intake based on the filtering parameter is initiated.

Object count estimation by live object simulation

Extending audience reach in messaging campaigns using super profiles

A system, method, apparatus and processor readable media are described for real-time prediction of an advertising audience volume through analysis of historical audience data, and tuning of the predicted audience volume. Embodiments enable a user to specify a query for audience volume prediction. Such a query may be a Boolean combination of various audience categories. A time range may be determined that indicates the amount of historical data that is to be analyzed to make the audience volume prediction in real time. Employing the user-specified query, an audience volume prediction may be provided for a future time period, based on an analysis of retrieved historical audience data for the time range. Embodiments may also enable a user to tune the predicted audience volume through modification of the query through one or more iterations.

Real time audience forecasting

A method, system, apparatus, and storage medium for determining that a client device is enabled for persistent identification, and that may operate as a filter for user information based on whether the client is enabled for persistent identification. A first communication is received regarding a request by the client for a web page. At least one application level data structure is then provided for storage by the client, that persistently identifies at least one characteristic of the client. A second communication is then received that includes a representation of the application level data structures provided, and a comparison is made between the data structures provided and the representation received to determine whether the client is enabled for persistent identification. If persistent identification is enabled, the client may then be provided with advertisements or other content related to the client interests or characteristics.

Filter for user information based on enablement of persistent identification

The present disclosure provides a detailed description of techniques used in methods, systems, and computer program products for simulating user web page visits to generate an advertising campaign target audience list. The claimed embodiments address the problem of efficiently and quickly processing voluminous amounts of user data to enable rapid initiation of an advertising campaign. More specifically, the claimed embodiments are directed to approaches for a receiving user web page visit records (e.g., user ID, URL, timestamp, etc.), preparing batches of the visit records, and iterating through the batches of visits to simulate a user's re-visit to the web page. The simulated user visits and associated user attributes (e.g., from on line and off line activities) can then be tested against advertising campaign specifications to generate a target audience list.

Simulating online user activity to generate an advertising campaign target audience list

A system, method, and computer program product for reducing web page load latency by scheduling sets of successive outgoing HTTP calls. Some embodiments commence upon receiving from a requesting client device, a request for content of a web page, wherein the content comprises two or more portions of dynamic content. Operations are performed to determine that the two or more portions of dynamic content are to be processed separately. A scheduling script to be executed by the requestor is generated and sent to the client device. The scheduling script comprises instructions to process a first subset of the two or more dynamic portions of content and also comprises instructions to process a second subset of the two or more portions of dynamic content. The scheduling script, when executed by requesting client device, causes the first subset of dynamic content and the second subset of dynamic content to be processed separately.

Reducing web page load latency by scheduling sets of successive outgoing HTTP calls

An electronic auction system known as the Yahoo! Auction System provides functionality that permits users to conduct auction transactions with various payment units, such as incentive points and credit points, as well as money. Points can be earned in a variety of ways and redeemed via online auctions. The Yahoo! Auction System includes a web server, a messaging server, a database server, and various databases including an account database for storing information about account balance, expiration date for each point or group of points, and redemption information. The Yahoo! Auction System provides different auction formats, such as Standard Auction, Dutch Auction, Progressive Auction, Buy-or-Bid Auction, and Declining Bid Auction. The Yahoo! Auction System reserves the bid amount associated any new valid bid in the bidder's account and unreserves those bid amounts that were previously reserved but are no longer the winning bid or otherwise displaced from the top bid positions.

Auction redemption system and method

Growing community of inventors

Santa Cruz, CA, United States of America

John Patrick Connelly