Search Query Hinting and Segmentation for Social Networking
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Solution Overview
Problem
Social networking systems face inefficiencies in generating search results due to complex queries and large datasets, leading to inadequate results and processing inefficiencies, particularly when inner and outer query constraints intersect.
Innovation Solution
The implementation of structured queries with query hinting and inverse operators, such as the 'weak and' (WAND) and 'strong or' (SOR) operators, and the use of scoring and ranking based on search intent, to refine search results and improve processing efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If complex structured queries with multiple constraints are processed using traditional search methods, then comprehensive search coverage is achieved, but processing efficiency deteriorates and results become inadequate
Solution Approach 1:
The query processing system segments complex structured queries into multiple simpler sub-queries that can be processed independently. Each sub-query handles a specific aspect of the original query, allowing parallel processing and reducing the computational burden on any single processing unit. This segmentation enables the system to maintain comprehensive search coverage while significantly improving processing efficiency.
Solution Approach 2:
The system performs preliminary actions by pre-computing and caching intermediate results for frequently accessed data subsets. When a complex query is received, the system can leverage these pre-computed results to avoid redundant processing, thereby improving query processing efficiency without compromising the comprehensiveness of the final results.
2Device complexity
If traditional search operators are used without query hinting, then simple query processing is maintained, but search result relevance deteriorates for complex queries
Solution Approach 1:
Query hinting acts as an intermediary mechanism between the user's search intent and the query processing system. Hints provide additional contextual information that guides the search process, enabling the system to generate more relevant results for complex queries without significantly increasing processing complexity. The hints serve as mediators that bridge the gap between simple query structures and complex search requirements.
3Speed
If inverted index structures are used for fast retrieval, then processing speed is improved, but accuracy deteriorates when dealing with complex constrained queries
Solution Approach 1:
The retrieval process is segmented into multiple stages: an initial fast retrieval phase using inverted indexes to quickly identify candidate results, followed by a refinement phase that applies complex constraints to filter and rank results accurately. This segmentation allows the system to benefit from the speed of inverted indexes while maintaining the accuracy required for complex constrained queries through subsequent processing steps.
Data Source
AI summary
In one embodiment, a method includes receiving a query comprising one or more n-grams, generating a plurality of query commands based on a parsing of the query input, wherein each query command comprises an inner query constraint and an outer query constraint, scoring the query commands based at least in part on a number of objects matching the inner query constraint of the respective query command, selecting a first query command based at least in part on the respective scores of the query commands, and executing the first query command to identify a plurality of objects based on: (1) a first set of objects matching the first inner query constraint and at least in part matching the first outer query constraint, and (2) a second set of objects matching the first outer query constraint.