Targeted Information Provision via Application List Analysis
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Solution Overview
Problem
Current technologies lack an efficient method to provide targeted information to users based on their application installation lists on devices, limiting personalized content delivery and revenue generation models for mobile webpages.
Innovation Solution
A system and method that collects user identifiers and application lists, extracts text information from these lists using theme analysis, and selects user identifiers with corresponding keywords to provide targeted information, enabling personalized content delivery and revenue sharing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If generic content is provided to all users, then system complexity is low and implementation is simple, but user engagement and revenue generation are limited
Solution Approach 1:
The system performs preliminary actions by collecting user identifiers and application list information in advance, storing them in a database before content delivery. This pre-collection enables subsequent targeted content provision without adding complexity at the moment of content delivery, thus improving revenue generation while maintaining system simplicity.
Solution Approach 2:
The patent introduces an intermediary processing system that includes a collector, database, extractor, and selector. This intermediary layer processes user information and matches it with relevant content, enabling targeted content delivery that improves revenue without requiring complex modifications to the basic content delivery infrastructure.
2Measurement precision
If user information is collected and processed for targeted content, then personalized content delivery improves, but information processing time and system complexity increase
Solution Approach 1:
User identifiers and application list information are collected and stored in a database in advance, before the content matching process occurs. This preliminary data collection eliminates the need for real-time information gathering during content delivery, thereby reducing processing time while maintaining high targeting accuracy.
Solution Approach 2:
The system segments the information processing into distinct functional modules: a collector for gathering data, a database for storage, an extractor for retrieving relevant information, and a selector for matching content. This segmentation allows each module to operate efficiently and independently, reducing overall processing time while achieving precise user targeting.
3Adaptability or versatility
If application list information is analyzed for each user, then content personalization improves, but computational resources and processing complexity increase
Solution Approach 1:
The patent divides the complex task of analyzing application lists into separate functional components: collection of user identifiers, separate collection of application lists, extraction of relevant information, and selection of matching content. This segmentation reduces processing complexity by allowing each component to handle a specific task efficiently rather than requiring a single complex processing system.
Solution Approach 2:
The system introduces an intermediary processing layer with specialized components (collector, database, extractor, selector) that mediates between raw user data and final content delivery. This intermediary structure simplifies the overall processing complexity by providing clear interfaces and dedicated functions for each processing stage, enabling effective content personalization without overwhelming computational requirements.
Data Source
AI summary
A method and system for providing target information through an application list includes collecting user identifiers to identify each users and application lists of applications installed on terminals of the users; extracting text information using the application list for the user identifiers; and selecting a user identifier having text information corresponding to a keyword from among the user identifiers.