Ebay, Incorporated

Paypal, Inc.

Microsoft Technology Licensing, LLC

Linkedin Corporation

Dhanurjay A S Patil

Grahame Andrew Jastrebski

Chris Riccomini

Allison Elizabeth Miller

Abhishek Gupta

Peter Nicholas Skomoroch

Matthew Terence Hayes

Hugo Olliphant

George Lee

Timothy Michael Murphy

Brian Andrew Phillips

Daniel L Pritchett

In some example embodiments, a system and method are provided for graph pattern analysis. In example embodiments, pattern data of a primary network that includes data relating to relationships between entities are received. A reference matrix comprising a plurality of secondary network determined based on the pattern data of the primary network is generated. A graphical display of the primary network and the reference matrix are displayed on a user interface. A selection of a secondary network from the plurality of secondary networks of the reference matrix is received. The selected secondary network has similar matching characteristics with at least a portion of the primary network. In response to the selection, the primary network is classified as a classification type related to the selected secondary network.

System and method for graph pattern analysis

In an example, disclosed is a machine automated method of identifying a set of skills. In some examples, the method includes extracting a plurality of skill seed phrases from a plurality of member profiles of a social networking site, creating a plurality of disambiguated skill seed phrases by disambiguating the plurality of skill seed phrases using one or more computer processors, and de-duplicating the plurality of disambiguated skill seed phrases to create a plurality of de-duplicated skill seed phrases.

Skill extraction system

In one example embodiment, a system and method is shown as including identifying a context set data defining a context within which a person resides. Next, an operation is executed so as to retrieve the context set data that includes person data and relationship between persons data, the relationship between persons data including certain characteristics that define the person in the context set. An operation may be executed so as to perform a set operation on the person in the context set so as to generate a graph set. Further, an operation may be executed to render a graphical representation of the context set.

Methods and systems to generate graphical representations of relationships between persons based on transactions

This document discusses, among other things, a system and method for detecting an initiation of a transaction and generating a string of characters based on the detection. A subset of characters of the string of characters is presented in such a way as to be distinguished from remaining characters of the string of characters. In various example embodiments, the transaction is validated based on an identification of the subset of characters of the string of characters.

System and method for key challenge validation

In some example embodiments, a system and method are provided for graph pattern analysis. In example embodiments, pattern data of a primary network that includes data relating to relationships between entities are received. A secondary network based on the pattern data of the primary network is generated by using an algorithm that processes pattern characteristics extracted from the pattern data. The generated secondary network is provided for further analysis.

A system and method for providing key challenge validation is provided. In example embodiments, an initiation of a transaction is detected and a challenge comprising a string of characters is generated based on the detection. The string of characters includes transaction specific information indicating a detail of the transaction. The challenge is presented whereby the string of characters includes a challenge key. A response to the challenge is received that includes the challenge key. In various example embodiments, the transaction is validated based on an identification of the key challenge of the string of characters.

In some example embodiments, a system and method is illustrated as including retrieving account data including at least one of an account identifier and transaction data. Further, in some example embodiments, a data structure is generated that includes the account data. Additionally, in some example embodiments, the data structure is sorted where the data structure includes the account data to create a sorted account data structure. In some example embodiments, a sorted account data structure is displayed.

Transaction data representations using an adjacency matrix

This document discusses, among other things, a system and method for detecting an initiation of a transaction and generating a string of characters based on the detection. A first portion of the string of characters may be presented in such a way as to be distinguished from a second portion of the string of characters. In various example embodiments, the transaction is validated based on an identification of the first portion of the string of characters.

System and methods for key challenge validation

In some example embodiments, a system and method are illustrated as including receive pattern data that includes transaction data relating to transactions between persons. Next, the system and method may include building at least one secondary network based upon the pattern data. Additionally, the system and method may include displaying the at least one secondary network.

Graph pattern recognition interface

In one embodiment, a system and method is illustrated as including generating a model using at least one of a global conduct score and attribute data. A range of numeric values may be retrieved, based upon which, a better term is granted in a transaction than would otherwise be granted in the transaction. A comparison may be made between the model and the range of numeric values. Further, a better term may be granted in the transaction where the model falls within the range of numeric values. The global conduct score is computed using an approach including at least one of a feed score approach, and a composite score approach. The attribute data includes page view data, click through data, account usage data, and good purchased data. The model includes a global conduct score model, a weighting model, an AI based model, and an associated network based model.

Growing community of inventors

Belmont, CA, United States of America

Dhanurjay A S Patil