Content Filtering via Canonical Form Standardization
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Solution Overview
Problem
Current content filtering methods are inefficient in real-time scenarios, particularly when children create content, as they often subvert traditional blacklists by modifying words, leading to exponential growth in the blacklist size and increased computing resources needed, making real-time filtering costly and impractical.
Innovation Solution
A system that preprocesses input to standardize and compare it against a smaller blacklist by converting text into canonical form, removing whitespace and punctuation, and checking for symbol substitutions, allowing for real-time filtering of inappropriate content by maintaining a smaller blacklist.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional blacklist filtering is used to block inappropriate content, then content filtering effectiveness is improved, but the blacklist size grows exponentially and computational resources increase
Solution Approach 1:
The system performs preliminary processing of the blacklist entries before comparison, converting them into standardized canonical forms. This preprocessing step eliminates variations in capitalization, spacing, and formatting, allowing the system to maintain a smaller, more efficient blacklist while still effectively identifying inappropriate content regardless of how users attempt to modify it.
Solution Approach 2:
The invention changes the parameters of blacklist storage by storing only canonical standardized forms rather than all possible variations. By transforming the representation of filtered terms into a normalized parameter set (canonical form with consistent casing, spacing, and formatting), the system reduces blacklist size exponentially while maintaining filtering effectiveness through real-time standardization of user input.
2Reliability
If traditional blacklist filtering is used to block inappropriate content, then content filtering effectiveness is improved, but computational resources and processing time increase
Solution Approach 1:
The system performs preliminary processing of the blacklist entries before comparison, converting them into standardized canonical forms. This preprocessing step eliminates variations in capitalization, spacing, and formatting, allowing the system to maintain a smaller, more efficient blacklist while still effectively identifying inappropriate content regardless of how users attempt to modify it.
Solution Approach 2:
The invention replaces the mechanical approach of storing and comparing every possible variation of inappropriate terms with a computational transformation approach. By applying standardization algorithms to convert user input into canonical forms and comparing against a reduced blacklist, the system achieves faster processing speeds suitable for real-time filtering while maintaining comprehensive coverage.
3Adaptability or versatility
If users can modify words to circumvent filtering, then user freedom is improved, but filtering reliability deteriorates
Solution Approach 1:
The invention changes the parameters of blacklist storage by storing only canonical standardized forms rather than all possible variations. By transforming the representation of filtered terms into a normalized parameter set (canonical form with consistent casing, spacing, and formatting), the system reduces blacklist size exponentially while maintaining filtering effectiveness through real-time standardization of user input.
Solution Approach 2:
The system implements a feedback mechanism where user input is standardized and compared against the canonical blacklist forms. When modifications are detected (such as altered capitalization, spacing, or formatting), the standardization process transforms them back to their canonical forms for comparison, providing feedback that maintains filtering reliability while allowing users to express themselves in various ways.
Data Source
AI summary
Systems and arrangements are provided for filtering language. As presently preferred, these are configured to filter inappropriate language, symbols, words, etc on web sites or used in chat rooms. Embodiments create one or more arrays of inappropriate character strings representing, for example, obscene words and character combinations. Embodiments identify the inappropriate character strings, for example in chat text, and edit them to an appropriate form, for example with cartoon characters, and/or delete the inappropriate character strings. Preferably, at least one embodiment applies the content filter via executing a program of instructions, stored on a tangible storage medium, to achieve this functionality.