Anomaly Detection for Personalized Advertising Efficiency

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Solution Overview

Problem

Existing advertising methods lack personalization, often annoying users who do not need the advertised products, leading to low efficiency and potential legal risks due to intrusive profiling, and fail to accurately target user demand.

Innovation Solution

A system that detects anomalies in user environments and devices, using real-time parameter collection and state modeling to identify actual user needs, providing targeted notifications about relevant products or services as solutions to detected problems, without requiring additional modules.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If traditional advertising methods are used to reach undefined groups of people, then advertising coverage is broad, but advertising efficiency is low and user annoyance increases

Engineering Contradiction:
Improveadvertising efficiencyVSAvoiduser annoyance
Core Design Contradiction:
ProductivityVSObject-affected harmful factors

Solution Approach 1:

The patent segments the undefined user group into specific target audiences based on profiling data, behavior patterns, and demographic characteristics. This segmentation enables personalized advertising delivery to relevant users only, improving efficiency while reducing annoyance to non-target users who receive no advertisements.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The patent performs preliminary user profiling and segmentation before advertising delivery. By pre-analyzing user characteristics, behaviors, and preferences, the system prepares targeted advertising content in advance, ensuring that only relevant users receive advertisements, thereby improving efficiency and reducing user annoyance.

Inventive Principle:
Principle #10Preliminary action

2Productivity

If personalized targeted advertising is implemented based on user profiling, then advertising efficiency improves, but legal risks increase due to information gathering and profiling

Engineering Contradiction:
Improveadvertising efficiencyVSAvoidlegal risks
Core Design Contradiction:
ProductivityVSObject-affected harmful factors

Solution Approach 1:

The patent introduces an intermediary layer between raw user data and advertising delivery. This intermediary performs anonymization, aggregation, and ethical filtering of profiling data, ensuring that personal information is processed in compliance with legal requirements while still enabling effective targeted advertising through aggregated insights.

Inventive Principle:
Principle #24Intermediary (Mediator)

3Area of stationary object

If advertising is delivered through multiple channels and applications, then advertising reach increases, but user intrusion and avoidance behavior increase

Engineering Contradiction:
Improveadvertising reachVSAvoiduser intrusion
Core Design Contradiction:
Area of stationary objectVSObject-affected harmful factors

Solution Approach 1:

The patent applies local quality by delivering different advertising content and frequencies to different user segments based on their specific characteristics, preferences, and engagement patterns. This personalized approach ensures that advertising is relevant and non-intrusive for each user, maintaining reach while reducing intrusion and avoidance behavior.

Inventive Principle:
Principle #3Local quality

Data Source

PatentEP3675018A1Method of detecting compatible systems for systems with anomalies
Publication Date: 2020.07.01 AO KASPERSKY LAB
  • EP3675018A1 patent drawingFigure 1
  • EP3675018A1 patent drawingFigure 2A
  • EP3675018A1 patent drawingFigure 2B

AI summary

Systems and methods are provided for detecting system anomalies and detecting compatible modules for replacing computing systems. The described technique includes receiving system parameters specifying functionality of a first computing system, and interrogating a state model using the received system parameters to detect an anomaly within the first computing system. Responsive to detecting an anomaly in the first computing system based on the state model, the system re-interrogates the state model based on at least one candidate module such that the system parameters of the first computing system are replaced by equivalent system parameters of the candidate module. The system then selects the at least one candidate module based on a determination that the candidate module is compatible with the first computing system, and that no anomaly was detected during the repeat interrogation of the state model using the system parameters of the candidate module.