Contextual Query Generation from Displayed Content
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Solution Overview
Problem
Current interaction models require users to input queries to retrieve contextual information, which can be time-consuming and prone to errors, especially when users need information about a displayed resource without typing or speaking.
Innovation Solution
A system that generates multiple queries from displayed content, determines quality scores based on visual appearance and user engagement, and provides user interface elements for selected queries, allowing users to access contextual information without inputting queries, thus reducing errors and improving efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users input queries manually to retrieve contextual information, then the information retrieval can be targeted and specific, but the process becomes time-consuming and error-prone
Solution Approach 1:
The system performs preliminary actions by automatically generating multiple candidate queries from the displayed content before the user needs to search. The system extracts entities, relationships, and contextual information from the current page to pre-formulate relevant search queries, eliminating the need for users to manually input queries and reducing both time and errors.
Solution Approach 2:
The system serves itself by automatically analyzing the displayed content and generating its own search queries without requiring user input. The system uses natural language processing and entity recognition to autonomously create queries that reflect the contextual information available on the current page, making the information retrieval process self-driven rather than user-driven.
2Ease of operation
If users manually input queries, then specific information needs can be addressed, but the process is prone to errors and requires multiple attempts
Solution Approach 1:
The system performs self-service by automatically generating queries from the displayed content without requiring user input. This eliminates manual typing errors and leverages the system's NLP capabilities to create accurate queries that reflect the actual contextual information on the page, thereby improving both ease of operation and query success rate.
Solution Approach 2:
The system uses feedback mechanisms by analyzing user interactions, click patterns, and engagement metrics to continuously improve query generation. The system learns from user behavior to refine its query formulation, ensuring that generated queries are more likely to succeed and better match user information needs over time.
3Loss of information
If multiple query attempts are made to find relevant information, then comprehensive results can be achieved, but processing resources are increased
Solution Approach 1:
The system performs preliminary analysis of the displayed content to pre-identify all relevant entities, relationships, and potential information needs before any search is executed. By generating multiple candidate queries in advance based on comprehensive content analysis, the system ensures information completeness is achieved in a single search operation rather than requiring multiple iterative attempts, thereby reducing processing resources.
4Ease of operation
If the system generates queries from displayed content, then user convenience is improved, but query quality may vary
Solution Approach 1:
The system performs preliminary quality assessment of generated queries by evaluating entities, relationships, and contextual relevance before presenting them to users. This pre-validation process ensures that only high-quality, relevant queries are generated from the displayed content, maintaining measurement precision while preserving ease of operation.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for providing contextual information to a user. In one aspect, a method includes receiving, from a user device, a query-independent request for contextual information relevant to an active resource displayed in an application environment on the user device, generating multiple queries from displayed content from the resource, determining a quality score for each of the multiple queries, selecting one or more of the multiple queries based on their respective quality scores, and providing, to the user device for each of the selected one or more queries, a respective user interface element for display with the active resource, wherein each user interface element includes contextual information regarding the respective query and includes the respective query.