Implicit Question Query Identification via Template Matching
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Solution Overview
Problem
Search engines face challenges in identifying implicit question queries, which are queries seeking answers without structured interrogative terms, leading to ambiguity in providing relevant information.
Innovation Solution
The method involves using query templates with variable and invariable terms to match and determine implicit question queries, generating synthetic templates, and validating these queries to identify and process implicit question queries without relying on extensive language models or machine learning solutions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If extensive language models or machine learned solutions are used to identify implicit question queries, then identification accuracy may improve, but implementation complexity and training time increase significantly
Solution Approach 1:
The patent segments the query identification process into template matching and behavioral analysis components, avoiding the need for a single complex language model. By breaking down implicit question identification into manageable template-based patterns, the system achieves accurate identification without extensive machine learning infrastructure.
Solution Approach 2:
The patent creates synthetic question queries by copying and transforming actual question queries through query templates. This synthetic data generation approach enables behavioral analysis and implicit question identification without requiring extensive real-world training data or complex language models.
2Reliability
If language models or machine learned models are used for implicit question query identification, then identification capability improves, but training errors and implementation time increase
Solution Approach 1:
The patent performs preliminary actions by pre-defining query templates and establishing behavioral analysis frameworks before actual query processing. This preparation work enables rapid identification of implicit questions without requiring time-consuming training sessions, as the system is pre-configured with templates and behavioral patterns.
Solution Approach 2:
The system uses actual user query behavior to automatically refine and improve its identification capability through behavioral analysis, eliminating the need for external training processes. The system serves itself by learning from observed user patterns rather than requiring manual training with language models.
3Measurement precision
If query templates learned from actual queries are used, then mapping accuracy to user intent improves, but system complexity increases
Solution Approach 1:
The patent creates universal query templates that can match multiple types of implicit question patterns across different domains. These templates serve multiple functions by capturing various question structures (what, where, when, who, why, how) through standardized patterns, reducing the need for domain-specific complex models while maintaining high mapping accuracy.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for identifying implicit question queries. In one aspect, a method includes receiving a query in unstructured form, comparing terms of the query to query templates, determining, based on the comparison, a match of the query terms to a first query template, wherein the first query template is not determined to be indicative of a question query, determining, based on the first query template, a second query template, and determining that the query is an implicit question query in response to the second query template being indicative of a question queries.