Search Query Optionalizing for Social Network Data
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Solution Overview
Problem
Current social-networking systems face inefficiencies in optimizing search queries due to rigid data storage structures that do not account for optional search terms, leading to suboptimal search results.
Innovation Solution
The method involves identifying optional search terms in a query and modifying them to improve search efficiency by sending the modified query to specific data stores while also executing the unmodified query across other data stores, thereby aggregating results and enhancing relevance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If search queries are executed against all data stores without modification, then comprehensive search coverage is achieved, but search efficiency and relevance deteriorate due to rigid data storage structures not accounting for optional search terms
Solution Approach 1:
The patent segments the search query execution process into multiple parallel paths: one path executes the modified query with optional terms removed against specific data stores, while another path executes the unmodified query against other data stores. This segmentation allows the system to tailor query execution to different data store types, improving both relevance and efficiency simultaneously
Solution Approach 2:
The system dynamically modifies search queries by identifying and removing optional search terms based on the target data store type. This dynamic adaptation transforms a rigid query execution approach into a flexible one that adjusts query structure in real-time based on the specific data store being queried, resolving the contradiction between comprehensive coverage and search efficiency
2Measurement precision
If optional search terms are removed from queries, then matching accuracy for specific object types improves, but query flexibility and coverage deteriorate
Solution Approach 1:
The patent implements a universal query execution framework that handles both modified and unmodified queries through the same system architecture. This multi-functional approach allows the search system to maintain both precise matching (through modified queries) and broad coverage (through unmodified queries) simultaneously, resolving the contradiction between accuracy and versatility
3Reliability
If the system executes both modified and unmodified queries, then search result quality improves, but system complexity and processing overhead increase
Solution Approach 1:
The patent segments the data store infrastructure into distinct types with dedicated query execution paths. This segmentation naturally divides the complexity, as each data store type has its own optimized query handling logic, making the overall complex system manageable and maintainable while still delivering high-quality results
Data Source
AI summary
In one embodiment, a method includes receiving a search query from a client system; modifying the search query by removing a first search term associated with a first object type from the search query; retrieving search results responsive to the modified search query from a first data store storing objects of the first object type; and sending one or more of the search results to the client system.