Implicit Search Query Generation via User Context Analysis
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Solution Overview
Problem
Conventional search engines require explicit user queries to access relevant information, often leading to missed opportunities for accessing potentially relevant data stored locally or globally due to user unawareness of available information.
Innovation Solution
The system generates multiple implicit search queries based on user context attributes, combining results from local and global indices to provide relevant information without explicit user input, using a query system that extracts keywords from user interactions and contextual events to execute searches and rank results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional search engines require explicit user queries, then search accuracy is improved, but information retrieval efficiency deteriorates due to user unawareness of available information
Solution Approach 1:
The system performs preliminary actions by proactively generating and executing search queries based on user context before the user explicitly requests information. The query generation module continuously monitors user activities (document editing, email composition, browsing) and automatically formulates search queries relevant to the user's current task, retrieving information in advance without waiting for explicit user input.
Solution Approach 2:
The system provides self-service by autonomously generating search queries, executing searches, and presenting results without requiring explicit user commands. The query generation module uses user context attributes (active application, recent actions, selected text) to self-determine what information the user likely needs, automatically managing the entire search process from query formulation to result presentation.
2Productivity
If the system generates multiple implicit search queries automatically, then information retrieval efficiency is improved, but device complexity increases due to multiple query generation and result combination processes
Solution Approach 1:
The system segments the complex task of information retrieval into distinct functional modules: a context analysis module that extracts user context attributes, a query generation module that creates search queries from context, an execution module that runs searches, and a result integration module that combines results. This segmentation allows each module to handle a specific aspect of the process, managing complexity through functional decomposition while maintaining high retrieval efficiency.
Solution Approach 2:
The query generation module serves multiple functions: it analyzes user context, generates search queries, selects appropriate search engines, and initiates searches. This multi-functionality reduces overall system complexity by consolidating related operations into a single versatile component rather than requiring separate specialized modules for each function.
3Loss of information
If the system combines results from multiple search queries, then completeness of information is improved, but loss of time increases due to executing multiple queries and integrating results
Solution Approach 1:
The system applies partial action by executing multiple search queries simultaneously in parallel rather than sequentially, and by presenting a curated subset of the most relevant results rather than displaying all possible matches. The result integration module combines results from multiple queries but prioritizes and displays only the top-ranked relevant information, avoiding the time cost of processing and presenting every possible result while maintaining information completeness.
Data Source
AI summary
Systems and methods for generating multiple implicit search queries are described. In one described system, a query system receives a user context attribute and generates a plurality of implicit search queries based at least in part on the user context attribute. The query system then receives result sets associated with each of the plurality of implicit search queries and combines the results for display to a user.