User Profile Creation via De-identified Data Aggregation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current data mining techniques face challenges in creating accurate user profiles due to the abundance of unavailable data and the general nature of available data, which is often insufficient for targeted marketing and advertising purposes.
Innovation Solution
A user profile creation platform that analyzes aggregate user behavior data, including internet usage, to determine keywords and affinity values using machine learning techniques, while ensuring user privacy through de-identification and aggregation of data across multiple devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If data aggregation and analysis techniques are used to create detailed user profiles, then marketing effectiveness and targeting precision are improved, but user privacy protection deteriorates
Solution Approach 1:
The patent introduces de-identified data as an intermediary between raw user data and profile analysis. Personal identifiers are removed or obscured before data is aggregated and analyzed, allowing marketing effectiveness to improve while user privacy is protected through this mediating layer of anonymization
Solution Approach 2:
The patent combines data from multiple devices and users to create aggregated profiles that represent general behavior patterns rather than individual identities. By merging data at the aggregate level rather than individual level, the system achieves better statistical accuracy for marketing while reducing the ability to identify specific users
2Measurement precision
If comprehensive user behavior data is collected across multiple devices, then profile accuracy and marketing targeting are improved, but data complexity and processing difficulty increase
Solution Approach 1:
The patent segments user behavior data by device, application, and interaction type before aggregation. This segmentation allows the system to process complex multi-device data systematically by breaking it into manageable components that can be analyzed separately and then combined to create comprehensive profiles
Solution Approach 2:
The patent transforms raw behavioral data into standardized parameters such as affinity scores, engagement metrics, and interaction frequencies. By changing the parameters from raw data formats to normalized metrics, the system reduces processing complexity while maintaining the ability to predict user behavior accurately
Data Source
AI summary
Disclosed is a computer implemented method of creating a profile of a user based on user behavior. The method may include receiving a plurality of Universal Resource Locators (URLs) corresponding to a plurality of webpages visited by the user. Further, the method may include retrieving content from each of the plurality of webpages based on the plurality of URLs. Furthermore, the method may include analyzing content from each of the plurality of webpages. Additionally, analyzing content from a webpage may include analyzing content corresponding to each content type present on the webpage. Further, the method may include identifying a plurality of keywords corresponding to the webpage based on the analyzing. Furthermore, the plurality of keywords may be associated with a plurality of affinity values. The plurality of keywords and the plurality of affinity values may constitute the profile of the user.