Search Term Correction via Input Phase Detection
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Solution Overview
Problem
Conventional search engines face challenges in accurately suggesting search terms when users input incorrect or incomplete terms due to mistyping, as they lack effective methods to detect and correct misinput characters or sequences.
Innovation Solution
A system and method that detect descending and ascending phases in user input sequences to identify misinput terms, calculate probabilities of correction based on historical data using a noisy channel model, and store these probabilities for future suggestions, enabling improved search term suggestions by correcting incomplete inputs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional search engines use database-based suggestion techniques to propose search terms, then search suggestions can be provided to users, but the system cannot accurately detect or correct misinput terms caused by user typing errors
Solution Approach 1:
The system performs preliminary analysis of user input sequences to detect misinput terms before final search term suggestions are generated. By identifying descending and ascending phases in the input sequence, the system corrects potential typing errors in advance, improving the reliability of search suggestions without adding significant complexity to the overall system architecture.
2Measurement precision
If the system monitors complete user input sequences to detect misinput terms, then accuracy of correction improves, but processing time and computational resources increase
Solution Approach 1:
The system segments the user input sequence into distinct phases (descending phase where characters are removed, and ascending phase where characters are added). By dividing the continuous input stream into these manageable segments, the system can efficiently detect misinput patterns without processing the entire sequence as a single unit, thus improving detection precision while reducing computational overhead and processing time.
3Reliability
If the system stores historical search term sequences with misinput probabilities, then future search suggestions become more accurate, but storage requirements increase
Solution Approach 1:
The system applies local quality by storing detailed misinput probability information selectively for specific term pairs rather than uniformly for all search terms. By identifying and storing correction probabilities only for detected misinput patterns (where descending and ascending phases occur), the system improves suggestion accuracy for problematic terms while minimizing overall storage requirements compared to storing complete historical data for all search terms.
Data Source
AI summary
Method, system, and programs for providing enhanced search term suggestions. A set of incomplete search terms indicating a sequence of search terms entered may be received. It may be detected that the sequence contains a descending phase followed by an ascending phase. In response to the detection, a pair of misinput term and corresponding corrected term may be identified in the set of incomplete search terms. A probability with respect to the misinput term is a misinput of the corresponding corrected term may be determined based on a historical context. Using such a probability, an incomplete search term containing the misinput term may be corrected. One or more proposed search terms may be determined based on the corrected incomplete search term for suggestion to the user.