Literacy-Aware Content Personalization Without Manual Word Replacement
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Solution Overview
Problem
Existing content personalization methods require manual user interaction to replace difficult words or phrases, which is tedious and does not guarantee understanding by the user, leading to degraded user experience.
Innovation Solution
A system and method for literacy-aware content personalization that includes determining a user's literacy level, modifying content items based on this level, and providing updated content to enhance comprehension.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual word replacement tools are used, then users can access content, but the process is tedious and time-consuming
Solution Approach 1:
The system performs preliminary actions by automatically detecting difficult words and generating replacement candidates before the user needs them. The literacy level is assessed in advance, and content is pre-modified with appropriate replacements, eliminating the need for manual intervention during content consumption.
Solution Approach 2:
The system enables self-service by automatically identifying difficult words, generating replacement suggestions, and applying modifications without requiring user interaction. The content adaptation process serves itself by autonomously completing tasks that previously required manual user effort.
2Adaptability or versatility
If online replacement tools are used, then users can obtain alternative words, but it is not guaranteed that replacements are understandable by the user
Solution Approach 1:
The system incorporates feedback mechanisms by assessing the user's literacy level and using this information to guide word replacement decisions. The literacy assessment provides feedback about the user's comprehension capacity, which is then used to select appropriate replacement words that match the user's understanding level.
Solution Approach 2:
The system changes parameters by adjusting word complexity based on the assessed literacy level. Instead of using fixed replacement rules, the system dynamically modifies the complexity parameter of replacement words to match the user's comprehension ability, ensuring reliable understanding.
3Ease of operation
If users manually select and replace words, then they can attempt to improve understanding, but user experience is severely degraded
Solution Approach 1:
The system extracts the complex task of word selection and replacement from the user's responsibilities. By automatically performing these functions, the system removes the burden of manual word manipulation from the user, simplifying the interaction while maintaining comprehension improvement.
4Productivity
If repetitive word replacement process is used, then users can try to understand difficult content, but the process is tedious and time-consuming
Solution Approach 1:
The system ensures continuity of useful action by automatically and continuously identifying and replacing difficult words throughout the content consumption process. Instead of interrupting the user with manual replacement tasks, the system maintains continuous content delivery with pre-processing replacements, improving productivity without time loss.
Data Source
AI summary
The present teaching relates to a method, system, and programming for content personalization. A request is received from a user to obtain a content item. Information indicative of a literacy-level of the user is obtained and the content item to be provided to the user is retrieved. The content item is modified by updating information included in the content item based on the literacy-level of the user to generate an updated content item. The updated content item is provided to the user in response to the request.