Query Completion via Suffix Analysis for Ambiguous Terms
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Solution Overview
Problem
Users often face difficulties in formulating queries that accurately represent their information needs, especially when terms are ambiguous or uncommon, leading to inadequate suggested query completions from search engines.
Innovation Solution
A method is developed to select suggested query completions by determining the prefix and suffix of a partial query, calculating suffix similarity scores for unique queries with different prefixes, and using completion scores to rank potential query completions, which includes identifying candidate queries with shared suffixes and calculating query popularity scores to enhance query completion suggestions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional query completion methods are used, then suggested completions can be provided quickly, but the suggestions become meaningless when terms are ambiguous or uncommon
Solution Approach 1:
The query is divided into prefix and suffix components, allowing the system to analyze only the relevant suffix portion for completion suggestions. This segmentation enables meaningful completions by focusing on the ambiguous or uncommon terms (suffix) rather than the entire query, thereby improving reliability without requiring analysis of all query components.
Solution Approach 2:
The system applies different processing strategies to different parts of the query. The suffix (containing ambiguous or uncommon terms) receives specialized analysis using suffix trees and similarity scoring, while the prefix is used only for filtering candidate completions. This local quality approach ensures meaningful suggestions for problematic terms while maintaining overall system efficiency.
2Measurement precision
If more comprehensive query analysis is performed to handle ambiguous terms, then suggestion accuracy improves, but processing time increases
Solution Approach 1:
Suffix trees and completion candidates are pre-computed and stored during system initialization or background processing. When a user enters a query, the system only needs to extract the suffix and perform limited similarity matching against pre-organized data, rather than performing comprehensive analysis in real-time. This preliminary action significantly reduces processing time while maintaining high accuracy for ambiguous terms.
Solution Approach 2:
The system extracts only the necessary information (suffix portion) from the query for detailed analysis, while using the prefix only for filtering. By taking out the problematic ambiguous terms and analyzing them separately through suffix trees, the system achieves high accuracy without processing the entire query comprehensively, thus reducing overall processing time.
3Ease of operation
If query completion suggestions are provided for all possible terms, then user convenience improves, but the system becomes less reliable for uncommon terms
Solution Approach 1:
Suffix trees serve as an intermediary data structure that maps suffix patterns to relevant completion candidates. This intermediary enables the system to provide convenient autocomplete suggestions for uncommon terms by efficiently navigating the suffix tree to find relevant completions based on observed usage patterns, thereby maintaining reliability while improving ease of operation.
Solution Approach 2:
The system uses feedback from query logs and usage patterns to continuously improve its completion suggestions. By analyzing which completions users actually select and which queries result in successful information retrieval, the system refines its suffix tree and similarity scoring algorithms, ensuring higher reliability for uncommon terms while maintaining user convenience.
Data Source
AI summary
A technology is described herein for identifying suggested query completions for a partial query based upon unique queries which have suffixes similar to the suffix of the partial query, but have prefixes which do not contain the prefix of the partial query. The technology described herein selects suggested query completions for the partial query based on terms occurring at the ends of the unique queries, in a manner which is not limited to past queries that include all of the terms in the partial query. As a result, meaningful suggested query completions that are likely to assist the user in completing a partial query can be provided in instances where terms in the prefix of the partial query are ambiguous or uncommon.