Content Personalization System Using Domain-Specific Data Packet Segmentation
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Solution Overview
Problem
Existing content delivery systems fail to provide personalized content to users with diverse backgrounds and interests, as they often present the same information to all users regardless of their domain or class, leading to inadequate understanding due to the lack of real-time modifications based on user domains.
Innovation Solution
A content personalization system categorizes original content into data packets by domain and categorizes users into classes based on parameters, identifying relevant content and modifying it by inserting or deleting packets to generate target content tailored to each class, incorporating presenter features for effective presentation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the same content is recommended for all users, then the system operation is simple, but the content relevance to different user domains deteriorates
Solution Approach 1:
The system segments content into multiple data packets organized by domain (technical, marketing, sales, executive) and segments users into different classes based on their domain preferences. This allows the system to deliver customized content combinations to different user classes while maintaining simple overall system operation through automated classification and packet selection.
Solution Approach 2:
The system dynamically modifies content in real-time by selectively inserting or deleting data packets based on the user's class and domain preferences. Instead of creating separate static content versions, the system dynamically assembles personalized content by adding relevant domain-specific packets and removing irrelevant ones, enabling adaptability without complex manual operations.
2Ease of manufacture
If content is pre-generated and static, then the manufacturing process is simple, but the adaptability to different user classes deteriorates
Solution Approach 1:
The system performs preliminary organization of content into domain-specific data packets during the content creation phase. While the full personalized content is not pre-generated, the building blocks (data packets) are prepared in advance by domain, enabling rapid real-time assembly and modification when users are classified, thus maintaining manufacturing simplicity while achieving adaptability.
Solution Approach 2:
The system changes content parameters dynamically by modifying which data packets are included based on user class parameters. Instead of creating entirely different static content versions, the system adjusts the content composition by changing the set of active data packets, enabling real-time adaptation while keeping the base content structure simple and reusable across all user classes.
3Adaptability or versatility
If the presenter asks the audience about their background and preferences, then the content personalization improves, but the time consumption increases
Solution Approach 1:
The system enables self-service personalization by automatically classifying users into domains (technical, marketing, sales, executive) and delivering appropriate content packets without requiring presenters to manually assess audience preferences. Users are automatically categorized and receive personalized content based on their class, eliminating the need for time-consuming audience questioning while maintaining high personalization quality.
Solution Approach 2:
The system uses feedback mechanisms to automatically determine user class and domain preferences, replacing manual presenter-audience interaction. By analyzing user characteristics and automatically selecting appropriate data packets based on this feedback, the system achieves effective content personalization without the time loss associated with traditional audience questioning and preference gathering.
Data Source
AI summary
Disclosed herein is a method and system for providing personalized content to a user. The method comprises categorizing original content to be provided to user into a plurality of data packets. The data packets include data of similar domain. The user is categorized into one of plurality of classes and a vocabulary of words suitable for the class is identified. The class is associated with a domain. The system identifies relevant content for the class. Thereafter, the system modifies the original content by either by inserting a new data packet or deleting a data packet. A target content is generated for the class based on vocabulary of words associated with class and modified original content. Thereafter, the target content is provided to the class by incorporating one or more features of a presenter for presenting the target content. The present disclosure enhances user experience by personalizing content for the user.