Social Network Query Construction via Grammar and Completion Tokens
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Solution Overview
Problem
Social networking systems face challenges in efficiently generating search queries within complex social graphs, as existing methods struggle to accurately and intuitively allow users to search for specific social-graph elements based on limited information.
Innovation Solution
A system that uses a multi-step implementation with a graphical interface and natural language search-query interface, allowing users to select grammar tokens and completion tokens based on social-graph elements, filtering out irrelevant options and providing relevant search results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a natural language search interface is used to allow users to search with limited information, then ease of operation is improved, but measurement precision deteriorates
Solution Approach 1:
The search query is segmented into multiple tokens (grammar tokens and completion tokens) that can be independently selected and refined. This allows the system to break down an imprecise natural language input into structured components, progressively building search accuracy while maintaining ease of use through incremental refinement.
Solution Approach 2:
The system performs preliminary actions by providing pre-determined grammar tokens and completion tokens based on the initial user input. These tokens are prepared in advance and presented to the user for selection, allowing the system to pre-process the search query and guide the user toward more precise search terms without requiring the user to formulate a complete search query from scratch.
2Measurement precision
If a multi-step query construction process is implemented to improve search accuracy, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The interface dynamically adapts to user input by generating and updating grammar tokens and completion tokens based on the selected grammar token. The system transitions from a static search interface to a dynamic multi-step construction process, where the available options and interface structure change based on user selections, allowing complexity to increase only when needed for precision.
Solution Approach 2:
Grammar tokens and completion tokens serve as intermediaries between the user's natural language input and the final structured search query. These tokens mediate the transformation process, breaking down the complex task of query construction into manageable steps with clear intermediate representations, thereby reducing the perceived complexity for the user.
3Loss of information
If completion tokens are filtered based on relevance to reduce information overload, then loss of information is reduced, but device complexity increases
Solution Approach 1:
The system changes parameters by filtering completion tokens based on their relevance to the selected grammar token. This parameter-based filtering (relevance scoring) automatically adjusts which tokens are presented to the user, reducing information overload while maintaining search precision. The filtering mechanism uses affinity calculations to dynamically adjust the set of available completion tokens.
Data Source
AI summary
In one embodiment, a method includes presenting, by a client system, grammar tokens, each grammar token being based on a natural-language string and comprising references to objects associated with an online social network, receiving, at the client system, a selection of one of the presented grammar tokens, the selected grammar token being based on a first natural-language string, presenting, by the client system, completion tokens, wherein each completion token is based on a natural-language string corresponding to the first natural-language string and comprises references to objects associated with the online social network, receiving, at the client system, a selection of one of the completion tokens, the selected completion token being based on a second natural-language string, and generating, by the client system, a structured query corresponding to the selected grammar and completion tokens, the structured query comprising references to the objects referenced in the selected grammar and completion tokens.