AI Query Correction System for Search Accuracy

The patent introduces an intermediary error correction system that includes a query analysis module, error identification module, correction module, and verification module. This intermediary system acts as a mediator between the user's input query and the search engine, automatically identifying and correcting errors such as typos, font errors, and information loss without requiring user intervention, thereby improving correction accuracy while managing system complexity through modular design

The patent replaces traditional mechanical error correction methods (manual user correction or simple spell-check) with an automated intelligent system that uses query analysis, error identification algorithms, correction strategies, and verification mechanisms. This substitution transforms the correction process from a manual or rule-based mechanical system to an automated system that can handle complex error types including typos, font errors, and information loss, significantly improving correction accuracy

The patent applies preliminary action by performing error correction before the search query is executed. The system analyzes the input query, identifies potential errors, generates corrected versions, and verifies them beforehand. This preliminary error correction ensures that the search is performed on accurate queries, improving search result reliability while minimizing time loss through efficient automated processing

The patent implements a feedback mechanism where the verification module checks the corrected query to ensure it maintains the user's original intent and improves accuracy. The system uses feedback from the verification process to refine corrections, and can adjust correction strategies based on whether the corrected query produces better search results, thereby improving reliability while managing processing time through iterative refinement

The patent applies local quality by focusing error correction efforts on specific segments of the query where errors are most likely to occur, rather than uniformly processing the entire query. The system identifies error-prone areas such as proper nouns, technical terms, and ambiguous phrases, and applies targeted correction strategies to these local segments. This approach achieves high correction coverage for critical areas while avoiding unnecessary processing of already-correct portions, thereby managing system complexity

The patent segments the query into multiple components including proper nouns, technical terms, and general phrases, and applies different correction strategies to each segment type. The query analysis module divides the input query into manageable parts, and the correction module applies specialized correction techniques to each segment based on its characteristics. This segmentation enables comprehensive error correction coverage across different error types while maintaining system complexity at manageable levels through modular processing