Privacy-conscious advertising via local preference matching

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Solution Overview

Problem

Current targeted advertising systems compromise user privacy by requiring access to extensive personal information to deliver relevant ads, which many users resist.

Innovation Solution

A method and network system where user preferences are stored locally on a user node, allowing comparison with meta-information in advertisement messages to determine relevance, enabling targeted advertising without revealing extensive personal information.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If targeted advertising uses user personal information to select relevant ads, then advertising efficiency and relevance are improved, but user privacy is compromised

Engineering Contradiction:

Improveadvertising efficiencyVSAvoiduser privacy

Core Design Contradiction:

ProductivityVSLoss of information

Solution Approach 1:

The patent extracts only the necessary meta-information from advertisements and compares it against user preferences stored locally on the user node, rather than requiring advertisers to access comprehensive personal information. This extraction approach allows targeted advertising while preserving user privacy by minimizing data exposure.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The user node acts as an intermediary between advertisers and users. It receives advertisement messages, compares their meta-information against locally stored user preferences, and determines relevance without requiring advertisers to access user personal information. This intermediary function enables targeted ads while maintaining privacy boundaries.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Productivity

If users reveal personal information to enable targeted advertising, then advertising relevance is improved, but user privacy control is reduced

Engineering Contradiction:

Improveadvertising relevanceVSAvoidprivacy control

Core Design Contradiction:

ProductivityVSEase of operation

Solution Approach 1:

The user node performs self-service by storing user preferences locally and autonomously comparing them against incoming advertisement meta-information. This eliminates the need for users to manually reveal personal information to advertisers, as the system serves itself by making relevance determinations based on pre-stored preferences.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

User preferences are stored locally on the user node in advance before advertising interactions occur. This preliminary storage of preferences enables the system to make relevance determinations immediately when advertisements arrive, without requiring real-time user input or revelation of personal information.

Inventive Principle:

Principle #10Preliminary action

3Productivity

If advertisers access extensive personal information for targeted ads, then ad effectiveness is improved, but user trust is reduced

Engineering Contradiction:

Improvead effectivenessVSAvoiduser trust

Core Design Contradiction:

ProductivityVSObject-affected harmful factors

Solution Approach 1:

The system extracts only essential meta-information from advertisements (such as topic categories or product types) and compares it against user preferences, rather than requiring advertisers to access extensive personal information. This extraction approach maintains ad effectiveness while preserving user trust by minimizing data access requests.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

Instead of advertisers accessing user personal information to determine ad relevance, the system inverts the approach by having users provide preferences that are stored locally, and then using those preferences to filter incoming advertisements. This inversion eliminates the harmful dynamic of advertisers probing for user data while maintaining effective targeted advertising.

Inventive Principle:

Principle #13The other way round (Inversion)

Data Source

PatentUS9508079B2Privacy-counscious advertising

Publication Date: 2016.11.29 NOKIA OF AMERICA CORP

AI summary

Various exemplary embodiments relate to a method and related network element including one or more of the following: receiving a plurality of advertisement messages via the communications network, each advertisement message of the plurality of advertisement messages including a set of meta-information which describes the content of an advertisement associated with the advertisement message; determining whether each advertisement message is relevant to the user by comparing the set of meta-information to a set of user preferences associated with the user, the set of user preferences stored locally on the user node; when an advertisement message is determined to not be relevant to the user, discarding the advertisement message; and when an advertisement message is determined to be relevant to the user, providing the user with access to the advertisement associated with the advertisement message.