Company Keyword Priority Scoring for People Search
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Solution Overview
Problem
On-line social networks face challenges in effectively prioritizing search results for company keywords, making it difficult to rank relevant profiles of professionals based on their employment, location, and other attributes, which affects user experience and growth.
Innovation Solution
A system utilizing a search engine optimization (SEO) framework that calculates priority scores for company keywords by combining signals from orthogonal data sources, including popularity, strength, and financial value, to enhance the relevance and importance of search results, thereby prioritizing profiles in the people search results pages (PSERPs).
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional search methods are used to rank profiles by employment history and education, then basic profile information is displayed, but relevant professional profiles based on company keywords do not appear at the top of search results
Solution Approach 1:
The patent changes the ranking parameters from basic profile attributes (employment history, education) to a comprehensive scoring system that incorporates company keyword priority scores, user engagement metrics, and profile relevance signals. This allows the system to dynamically adjust ranking based on multiple weighted parameters, improving the precision of relevance measurement while maintaining ease of operation through automated scoring.
Solution Approach 2:
The patent replaces traditional mechanical search ranking methods with an SEO-based scoring framework that uses automated signal processing and priority calculations. Instead of manual or simple algorithmic ranking, the system substitutes a sophisticated scoring mechanism that processes multiple data sources (company keywords, user interactions, profile attributes) to generate priority scores, thereby improving relevance without complicating user interaction.
2Measurement precision
If company keywords are prioritized using SEO framework with multiple data sources, then search result relevance is improved, but system complexity increases
Solution Approach 1:
The patent segments the complex prioritization system into distinct functional modules: company keyword extraction, priority score calculation, profile matching, and result ranking. Each module handles a specific aspect of the prioritization process, making the overall system more manageable despite its complexity. The segmentation allows independent optimization of each component while maintaining overall system coherence.
Solution Approach 2:
The patent introduces intermediary components such as priority score calculators and signal processing layers that mediate between raw data sources and final search results. These intermediaries transform complex multi-source data into standardized priority scores, simplifying the integration process and reducing system complexity by creating clear interfaces between different system components.
3Ease of operation
If profiles are prioritized based on multiple attributes including company keywords, then user experience is enhanced, but processing time and computational resources increase
Solution Approach 1:
The patent implements preliminary action by pre-calculating and storing company keyword priority scores and profile attributes in indexed formats before search queries are executed. This advance preparation allows the search system to quickly retrieve and compare pre-processed data during actual searches, significantly reducing processing time while maintaining enhanced prioritization based on multiple attributes including company keywords.
Solution Approach 2:
The patent applies local quality by optimizing different aspects of the search process for specific needs: company keyword matching uses pre-computed priority scores, while other profile attributes use indexed data structures. This localized optimization allows each attribute type to be processed efficiently according to its specific requirements, reducing overall processing time while maintaining comprehensive prioritization.
Data Source
AI summary
A search engine optimization system is provided with an on-line social network system. The on-line social network system includes or is in communication with a search engine optimization (SEO) system that is configured to prioritize company keywords (potential search terms) that represent respective people search results pages (PSERPs). The value of a company keyword is expressed as a priority score assigned to that company keyword. The SEO system generates priority scores for different company keywords, using a probabilistic model that takes into account a value expressing how likely the company keyword is to be included in a search query as a search term and/or a value expressing how likely is a search that includes the company keyword as a search term is to produce relevant results, as well as other signals that are indicative of the relative importance of a company represented by the company keyword.