# US 10,373,195 B2 · Methods and systems to evaluate and determine degree of pretense in online advertisement > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,373,195 B2 - Document ID: US10373195B2 - Status: Granted - Kind: B2 - Application number: 15/170,196 - Filed: 2016-06-01 - Published: 2016-12-08 - Granted: 2019-08-06 - Earliest claimed: 2015-06-02 - Assignees: The Nielsen Company (US), LLC - Applicants: The Nielsen Company (US), LLC - Inventors: Mohammad Ali Shiravi Khozani; Ehsan Mokhtari; Hadi Shiravi Khozani; Sergei Frankoff - Web page: https://patentgrep.com/patent/US10373195B2 ## CPC - G06Q 30/0248: {Avoiding fraud} - G06Q 30/0255: {based on user history} - G06Q 30/0277: {Online advertisement} - G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR ## Abstract Systems and methods are provided in the field of online advertising and malicious software. In some embodiments, a method for determining a degree of deceptiveness for a session is provided, the session having one or more relationships between one or more properties of interactions with an online advertisement, the method comprising: extracting one or more characteristics associated with each of the one or more relationships; applying one or more models to each of the one or more relationships to determine a degree of deceptiveness for each of the one or more relationships; aggregating the degree of deceptiveness for each of the one or more relationships to generate the degree of deceptiveness for the session. ## Claims ### Claim 1 A method of determining a degree of deceptiveness associated with a session presenting at least one online advertisement, the method comprising: capturing electronic interactions among at least two entities involved in the session, the captured interactions comprising interaction-related properties and time; defining one or more relations between the at least two entities involved in the session, the relations comprising an associated set of attributes; extracting, aggregating and filtering a plurality of attributes for the one or more relations from the captured electronic interactions, each attribute defining a data type and corresponding data value, wherein the extraction is performed by integration with the two or more entities; applying one or more models to each of the one or more relations; determining a degree of deceptiveness for each of the one or more relations based on the one or more applied models; and aggregating the degree of deceptiveness for each of the one or more relations; generating the degree of deceptiveness for the session based on the aggregated degree of deceptiveness for each of the one or more relations. ### Claim 2 (depends on 1) The method of claim 1, wherein the electronic interactions comprise at least one of user interactions, web-page rendering of the at least one online advertisement, publisher interactions and advertising network interactions. ### Claim 3 (depends on 1) The method of claim 1, wherein each of the one or more relations is defined based on different combinations of the interaction-related properties. ### Claim 4 (depends on 1) The method of claim 1, wherein the extracting uses at least one of a specially configured web browser and a web browser plug in. ### Claim 5 (depends on 1) The method of claim 1, wherein the extracting comprises analyzing integration of the at least one online advertisement with at least one of a publisher, a web page and an advertising technology network. ### Claim 6 (depends on 1) The method of claim 1, wherein the one or more models flag loading the at least one online advertisement on a web page, wherein the at least one online advertisement is loaded on a portion of the web page that is not viewable by a user. ### Claim 7 (depends on 1) The method of claim 1, wherein the extracting comprises extracting the plurality of attributes using a tracking pixel. ### Claim 8 (depends on 1) The method of claims 1, wherein the extracting comprises extracting the plurality of attributes using an ad-tracking tag. ### Claim 9 (depends on 1) The method of claim 1, wherein the extracting comprises extracting the plurality of attributes using a cookie. ### Claim 10 (depends on 1) The method of claim 1, wherein the one or more models are parametric models. ### Claim 11 (depends on 1) The method of claim 1, wherein the one or more models are non-parametric models. ### Claim 12 (depends on 1) The method of claim 1, wherein the one or more models comprise parametric and non-parametric models. ### Claim 13 (depends on 1) The method of claim 1, wherein the one or more models comprise an external model having a list of predetermined good or bad internet addresses, domains, publishers or advertisers. ### Claim 14 (depends on 1) The method of claim 1, wherein the associated set of attributes comprises historical attributes. ### Claim 15 (depends on 1) The method of claim 1, wherein aggregating the degree of deceptiveness for each of the one or more relations comprises taking a weighted average of the degree of deceptiveness for each of the one or more relations. ### Claim 16 A system for determining a degree of deceptiveness for a session presenting at least one online advertisement, the system comprising: a network infrastructure; a tracking server comprising a processor configured to: request tracking to capture electronic interactions among at least two entities involved in the session, wherein the tracking server is coupled to the at least two entities by the network infrastructure, wherein the captured interactions comprise interaction-related properties and time, define one or more relations between the at least two entities, wherein the relations comprise an associated set of attributes; extract a plurality of attributes for the one or more relations from the captured electronic interactions, each attribute defining a data type and corresponding data value, wherein the extraction is performed by integration with the two or more entities; receive the captured electronic interactions and the extracted plurality of attributes; determine the degree of deceptiveness for each of the one or more relations; and generate the degree of deceptiveness for the digital advertisement session based on the determined degree of deceptiveness for each of the one or more relations. ### Claim 17 (depends on 16) The system of claim 16, wherein the tracking server is configured to request tracking by delivering a tracking pixel to one or more of the at least two entities, wherein the tracking pixel comprises data indicative of a placement of the at least one online advertisement and the at least two entities. ### Claim 18 (depends on 16) The system of claim 16, wherein the tracking server is configured to generate and report static and dynamic metrics regarding a placement for the at least one online advertisement and the at least two entities using the extracted plurality of attributes. ### Claim 19 (depends on 16) The system of claim 16, wherein the captured electronic interactions comprise at least one of user interactions, web-page rendering of the at least one online advertisement, publisher interactions and advertising network interactions. ### Claim 20 A method for delivering content, the method comprising: receiving, at a tracking server, a request for a tracking pixel from a tag comprising code instructions to retrieve at least one online advertisement from an associated advertising server; receiving, at the tracking server, multiple data fields upon requesting the tracking pixel, the data fields comprising a campaign identifier, a client identifier, and a pixel type; logging, at the tracking server, the request for the tracking pixel with a timestamp, the campaign identifier, the client identifier, and the pixel type; executing the code embedded with the tracking pixel to capture attributes relating to at least one of placement of the at least one online advertisement, one or more entities with relations to the at least one online advertisement, and interaction between the one or more entities; and receiving, filtering and aggregating the captured attributes; generating a degree of deceptiveness and a report based on the aggregated captured attributes.