Third-Party Job Posting Ingestion via Data Model Mapping
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Solution Overview
Problem
Social network systems like LinkedIn only present job postings submitted by members, limiting exposure to job opportunities published on third-party systems.
Innovation Solution
Ingesting job postings from third-party systems into social network systems by identifying candidate mappings between data fields, generating data models, and publishing additional job postings based on these models, allowing for the integration of third-party content into the social network platform.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If job postings are only submitted by members through the social network system, then data quality and reliability are maintained, but the quantity and diversity of job opportunities are limited
Solution Approach 1:
The patent introduces an intermediary data ingestion system that acts as a bridge between third-party job posting sources and the social network system. This intermediary layer automatically extracts, validates, and transforms job posting data from external sources into the standardized format required by the social network, thereby increasing the quantity of available job postings while maintaining data reliability through systematic validation processes.
Solution Approach 2:
The patent replaces the manual mechanical process of member-submitted job postings with an automated electronic data ingestion system. This system uses algorithms to automatically crawl, extract, and import job posting data from third-party sources, eliminating the need for manual submission while implementing automated validation rules to ensure data quality and reliability.
2Ease of operation
If manual submission of job postings by members is required, then data accuracy is ensured, but the ease of operation and accessibility are reduced
Solution Approach 1:
The patent implements a self-service data ingestion system that automatically performs data extraction, validation, and integration without requiring manual intervention from members. The system autonomously accesses third-party job posting sources, extracts relevant information, validates the data against predefined criteria, and integrates it into the social network platform, thereby improving ease of operation while maintaining data precision through automated validation.
Solution Approach 2:
The patent creates standardized copies of job posting data from various third-party sources and transforms them into a unified format suitable for the social network system. This copying and standardization process automates data acquisition while ensuring consistency and precision through systematic data transformation and validation rules applied to each copied entry.
3Adaptability or versatility
If third-party job postings are integrated into the social network system, then the variety of job opportunities is increased, but the device complexity and data processing requirements increase
Solution Approach 1:
The patent segments the data ingestion process into distinct modular components: data extraction modules that access different third-party sources, validation modules that check data quality, transformation modules that convert data to standardized formats, and integration modules that import data into the social network system. This segmentation manages complexity by organizing the integration process into manageable, independent units that can be developed and maintained separately.
Solution Approach 2:
The patent implements a universal data ingestion framework that can handle multiple third-party job posting sources through a single standardized interface. The system uses configurable data extraction and transformation rules that can be applied across different sources, allowing the system to adapt to various data formats and structures without requiring separate custom integration processes for each source, thereby managing complexity while maintaining versatility.
Data Source
AI summary
A method of ingesting job postings into a social-networking system is disclosed. A candidate mapping is identified between a type of a data field corresponding to content items published on a third-party system and a type of a data field corresponding to job postings published on a social-networking system. A user interface is generated to prompt an administrator to identify the candidate mapping as a confirmed mapping. Based on the administrator identifying the candidate mapping as the confirmed mapping, the mapping is included in a data model corresponding to the content items published on the third-party system. Additional job postings to be published on the social-networking system are generated based on an application of the data model to additional content items published on the third-party system.