Ambiguous Query Disambiguation in Social Graph Search
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Solution Overview
Problem
Social networking systems face challenges in efficiently searching for elements within complex social graphs due to ambiguous terms in user queries, which can lead to incorrect matching of social-graph elements.
Innovation Solution
The system generates structured queries based on social-graph elements identified from ambiguous n-grams in user queries, allowing users to select the intended element and lock it, thereby refining the search process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the system uses simple text queries to search social graphs, then ease of operation is improved, but measurement precision deteriorates due to ambiguous terms
Solution Approach 1:
The system performs preliminary disambiguation by presenting multiple possible interpretations of ambiguous terms to the user before executing the search. This allows the user to select the intended meaning in advance, ensuring search accuracy while maintaining simple text query input.
Solution Approach 2:
The system introduces an intermediary disambiguation interface between the user's text query and the search execution. This intermediary presents structured queries with multiple choices, allowing the user to clarify their intent without changing the original simple text input method.
2Measurement precision
If the system generates multiple structured queries for ambiguous terms, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system generates multiple structured queries only when ambiguity is detected, rather than for all queries. This partial action approach maintains precision where needed while avoiding unnecessary complexity for unambiguous search terms.
Solution Approach 2:
The system automatically detects ambiguous terms and generates appropriate structured queries without requiring complex manual configuration. The disambiguation process is self-managing, reducing the burden on system operators while maintaining high search accuracy.
3Measurement precision
If the system presents structured queries to users for disambiguation, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The system performs disambiguation in advance by presenting structured queries before search execution. This preliminary action prevents incorrect search results and reduces the need for repeated searches, ultimately saving time despite the initial disambiguation step.
Solution Approach 2:
The system uses feedback from user selections of structured queries to refine and lock in the intended search meaning. This feedback mechanism ensures accurate search results while minimizing the need for multiple search attempts and corrections.
Data Source
AI summary
In one embodiment, a method includes receiving, from a client system, a character string having n characters entered by the first user into a query field, wherein a term comprising the nth character of the character string is an ambiguous term, identifying one or more objects corresponding to the ambiguous term based on a calculated probability that the ambiguous term corresponds to the identified objects, sending instructions for presenting a set of suggested queries to the first user, each suggested query from the set of suggested queries corresponding to one of the identified objects and comprising a reference to the corresponding identified object, receiving a selection of a suggested query corresponding to a first object of the identified objects, and sending, responsive to receiving the selection of the suggested query, instructions for modifying the ambiguous term in the query field to include a reference to the first object.