Automated Profile Ingestion via External Data Matching
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Solution Overview
Problem
Social networking services face challenges in maintaining complete and up-to-date member profiles, as users often forget to update their achievements, leading to incomplete information that hinders accurate searches and resume effectiveness.
Innovation Solution
The system automatically suggests and adds member profile attributes by ingesting information from publicly available network-based data sources, using extraction engines to create information records and machine learning algorithms to match this data with member profiles, prompting users to accept or reject suggested attributes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If users manually update their member profiles, then profile information can be kept complete and accurate, but users often forget to update their achievements leading to incomplete information
Solution Approach 1:
The system automatically updates member profiles by ingesting data from external network-based sources and matching it with member information, eliminating the need for manual user updates while maintaining profile completeness and accuracy
Solution Approach 2:
The system proactively gathers and prepares profile update information from external sources before presenting it to users, so that when users do interact with the system, the updates are already prepared and ready for review
2Measurement precision
If the system ingests data from multiple network-based data sources, then profile accuracy improves, but system complexity increases
Solution Approach 1:
The system employs a unified architecture that can ingest and process data from multiple different network-based data sources using a common framework, allowing the same system to handle diverse data sources without proportionally increasing complexity
Solution Approach 2:
The system uses an intermediary matching process that sits between data ingestion and profile updating, where extracted information is matched against existing member data before being applied, thereby managing complexity through a standardized intermediate processing layer
3Loss of information
If the system automatically suggests profile attributes, then profile completeness improves, but time required for user review increases
Solution Approach 1:
The system presents only the most relevant and high-confidence profile suggestions to users rather than all possible updates, reducing review time while still capturing the essential information needed for complete profiles
Data Source
AI summary
Disclosed in some examples are methods, systems, and machine-readable mediums which automatically determine network-based data sources for information ingestion and profile data completion. This method can be applied to automatically increase the library of network-based data sources utilized by the system to ingest profile information. This allows for more a complete tracking of member accomplishments and attributes and ultimately, allows for more complete member profiles. Before specific methods and systems for automatically determining network-based data sources are discussed, an overview of the process of ingesting information from network-based data sources and matching that information to members of the social networking service will be described.