Social Graph Search Query Filtering via Privacy-Aware Indexing
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Solution Overview
Problem
Current social networking systems face challenges in efficiently searching and analyzing complex social graphs for objects within their environment, particularly in generating personalized and structured search queries that respect privacy settings and provide accurate search results.
Innovation Solution
The system implements a method for generating structured search queries based on social-graph information, using typeahead processes to automatically match user inputs with existing nodes and edges, and bootstrapping to create new nodes and edges, while filtering results based on privacy settings and indexing social-graph data for efficient querying.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the system performs comprehensive search across the entire social graph, then search completeness is improved, but search efficiency and processing time deteriorate
Solution Approach 1:
The patent segments the social graph into multiple indexed data structures (e.g., user profiles, connections, interests, locations) that can be independently queried and combined. This segmentation allows the search system to efficiently navigate through organized portions of the graph rather than performing exhaustive searches across the entire complex structure, thereby maintaining search completeness while improving efficiency.
Solution Approach 2:
The system performs preliminary actions by pre-indexing social graph data into structured formats before search operations. The indexing process organizes user profiles, connections, interests, and other attributes in advance, enabling rapid retrieval and combination during search operations without requiring comprehensive traversal of the entire social graph at search time.
2Measurement precision
If the system generates highly personalized search results based on user profile, then result relevance is improved, but computational complexity increases
Solution Approach 1:
The patent applies local quality by tailoring search results to the specific user's profile attributes (interests, connections, demographics) while using standardized indexing and query processing mechanisms. Each user receives personalized results based on their local context without requiring complete reprocessing of the entire social graph, thus achieving high relevance with manageable computational complexity.
Solution Approach 2:
The system introduces an intermediary indexing layer that mediates between the raw social graph data and the personalized search results. The index structures serve as intermediaries that pre-process and organize data according to various attributes, allowing the search algorithm to efficiently combine relevant information without directly computing complex personalized results from the raw social graph for each query.
3Reliability
If the system filters search results based on privacy settings, then user privacy protection is improved, but search result quantity decreases
Solution Approach 1:
The system performs preliminary filtering based on privacy settings during the index construction phase. Privacy attributes are incorporated into the indexing structure in advance, allowing the search system to automatically apply privacy filters when querying indexed data without requiring post-processing of results. This approach ensures privacy protection while minimizing the impact on result quantity by only filtering out genuinely restricted data.
Data Source
AI summary
In particular embodiments, a method includes receiving, from a client system of a first user, a structured query comprising references to one or more objects associated with the online social network, identifying a set of target objects corresponding to the structured query, wherein each target object in the set is an object that is connected within the online social network to at least one of the objects referenced in the structured query, filtering the set of target objects based on a privacy setting of each of the connections to the target object, and generating search results comprising references to each target object from the post-filtered set that is connected to the first user within the online social network by a series of connections that have a visibility that is visible to the first user.