Selection List Auto-Correction via User Feedback Analysis
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Solution Overview
Problem
Current human-computer interfaces display all previous entries matching a user's input, including incorrect ones, which can lead to selecting incorrect options due to misspelled entries, and existing deletion methods are either unavailable to regular users or delete correct entries based on age or size thresholds.
Innovation Solution
A method and system that analyze user selections over time to identify and automatically delete entries with a high probability of being incorrect by calculating similarity distances using algorithms like N-grams and Damerau-Levenshtein, ensuring only correct entries are displayed in selection lists.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If all previous entries matching user input are displayed in selection list, then completeness of options is improved, but accuracy of selection deteriorates due to inclusion of incorrect entries
Solution Approach 1:
The system monitors user selections and feedback behavior (such as rapid re-selection or manual correction) to identify incorrect entries. When a user selects an entry and then quickly changes their selection or manually corrects it, the system uses this feedback to detect and remove the incorrect entry from future suggestions, thereby maintaining both completeness and accuracy of the selection list.
Solution Approach 2:
The system automatically detects and removes incorrect entries from the selection list without requiring manual intervention from users. By analyzing selection patterns and user behavior, the system self-corrects its suggestion list, eliminating the need for users to manually delete incorrect entries while maintaining the completeness of valid options.
2Reliability
If manual deletion of incorrect entries is allowed, then accuracy of selection is improved, but ease of operation deteriorates due to complexity of deletion process
Solution Approach 1:
The system automatically performs the deletion of incorrect entries without requiring user action. By monitoring selection patterns and user feedback, the system identifies and removes incorrect entries autonomously, eliminating the need for users to navigate complex deletion interfaces while maintaining high accuracy in the selection list.
Solution Approach 2:
The system uses user feedback (such as rapid re-selection or manual correction) to automatically trigger deletion of incorrect entries. This feedback mechanism allows the system to self-correct without requiring users to manually delete entries, thus maintaining accuracy while preserving ease of operation.
3Device complexity
If automated deletion based on age or size threshold is implemented, then device complexity is reduced, but reliability deteriorates due to deletion of correct entries
Solution Approach 1:
Instead of using simple age or size thresholds, the system employs feedback from user selections and behavior to determine which entries to delete. This feedback-based approach maintains reliability by ensuring that only genuinely incorrect entries are removed, while preserving correct entries regardless of their age or position in the list.
Solution Approach 2:
The system performs preliminary analysis of user selection patterns and feedback before deleting any entries. By pre-evaluating the correctness of entries based on user behavior data, the system ensures that only incorrect entries are removed, avoiding the deletion of valid entries that might occur with simple threshold-based approaches.
Data Source
AI summary
A computer implemented method and apparatus for managing a selection list include accessing previous entries in the history log for a particular field and displaying such entries in a selection list pull-down menu. A determination is made whether the selection is related to other recently made selections. Items from the selection list that are considered to be incorrect may be automatically deleted.