Social Network Search Entity Indexing for Result Reliability
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Solution Overview
Problem
Social networking systems face challenges in effectively prioritizing search results based on the reliability and authority of content object authors, leading to users encountering irrelevant or untrustworthy information.
Innovation Solution
The system identifies primary entities matching text queries and related entities through related-entity indexes, scores posts based on social signals, and prioritizes search results from authoritative sources, enhancing the relevance and reliability of search outcomes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system prioritizes search results from authoritative sources using related-entity indexes and social signals, then the reliability and trustworthiness of search results is improved, but the device complexity increases due to the need for maintaining entity indexes and scoring mechanisms
Solution Approach 1:
The system performs preliminary actions by pre-computing and maintaining related-entity indexes that map entities to their related entities before search queries are submitted. This allows the search system to quickly retrieve relevant content from authoritative sources without performing complex real-time analysis, thereby improving reliability while managing system complexity through advance preparation
Solution Approach 2:
The patent introduces related-entity indexes as intermediary data structures that mediate between the search query and the actual content retrieval. These indexes act as a bridge that pre-organizes relationships between entities, allowing the system to efficiently identify content from authoritative sources without directly implementing complex relationship analysis during the search operation itself
2Measurement precision
If the system performs comprehensive entity matching and related-entity identification, then the accuracy of search results is improved, but the loss of time increases due to the additional processing required
Solution Approach 1:
The system pre-computes related-entity indexes that store pre-analyzed relationships between entities, so that during search operations, the system can quickly retrieve and match entities without performing time-consuming relationship analysis in real-time. This preliminary preparation maintains high accuracy while significantly reducing search processing time
Solution Approach 2:
The search process is segmented into distinct phases: entity identification, related-entity lookup using pre-computed indexes, and result scoring. By dividing the comprehensive entity matching process into manageable segments with pre-computed components, the system achieves accurate results without the full time cost of performing all analysis from scratch for each query
Data Source
AI summary
In one embodiment, a method includes receiving a text query comprising one or more n-grams inputted by a first user, identifying one or more primary entities matching one or more n-grams of the received text query, and identifying, for each of the identified primary entities, one or more related entities based on one or more related-entity indexes associated with the primary entity. The method also includes accessing, for each identified related entity, one or more posts authored by the identified related entity, each accessed post matching all of the n-grams of the received text query, calculating a score for each of the accessed posts, and sending to the first user one or more search results corresponding to one or more of the accessed posts having scores higher than a threshold score, respectively.