Phrase Extraction for Digital Page Optimization
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Solution Overview
Problem
Digital pages of users on online services often lack relevant data, leading to diminished accuracy, relevancy, and completeness of search results, causing users to spend more time searching and consuming additional electronic resources, with no convenient and efficient way to add relevant data to their pages.
Innovation Solution
A system and method that identifies job postings matching a user's interests, extracts relevant phrases, determines optimal page sections for placement, and generates recommendations for adding these phrases, allowing users to efficiently enhance their page content through a user interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users manually add relevant data to their digital pages, then the accuracy and relevancy of search results improve, but the time and effort required from users increases
Solution Approach 1:
The system automatically extracts phrases from job postings and adds them to user profiles without requiring user intervention. The phrase extraction system serves itself by identifying relevant keywords and autonomously populating user digital pages, eliminating the need for users to manually add data while maintaining high accuracy in search results.
Solution Approach 2:
The system performs preliminary phrase extraction from job postings before users need to search or add data. By pre-populating user digital pages with relevant phrases from matched job postings, the system prepares the data in advance, so when users perform searches, the accurate data is already available without requiring users to spend time adding it manually.
2Loss of information
If users spend more time searching for relevant data, then they can find more complete information, but the computational resources and network bandwidth consumed increase
Solution Approach 1:
The system pre-computes and stores relevant phrases from job postings in user profiles before searches are executed. This preliminary population of data ensures that when searches occur, the server can quickly retrieve pre-processed information rather than performing extensive real-time computations, reducing computational expense while maintaining completeness of results.
Solution Approach 2:
The system extracts only the essential relevant phrases from job postings and stores them in user profiles, separating the critical information from the full job posting content. This extraction approach allows the system to maintain complete and accurate search results while minimizing the amount of data that needs to be processed and transmitted during searches, thereby reducing network bandwidth and computational resource consumption.
3Ease of operation
If the system provides automated phrase extraction and recommendation features, then the ease of operation for users improves, but the device complexity increases
Solution Approach 1:
The phrase extraction system operates autonomously without requiring user configuration or intervention. It automatically identifies relevant phrases from job postings, determines their placement in user profiles, and updates digital pages. This self-service approach simplifies the user interface and operation while the complexity is contained within the automated extraction engine, which runs in the background without user awareness.
Solution Approach 2:
The system introduces an automated phrase extraction intermediary layer between job postings and user profiles. This intermediary automatically processes job posting data, extracts relevant phrases using natural language processing, and integrates them into user digital pages. The complexity is isolated in this intermediary component, while users interact only with the simplified interface that shows recommendations and allows one-click acceptance.
Data Source
AI summary
Techniques for improving the accuracy, relevancy, and efficiency of a computer system of an online service by providing a user interface to optimize a digital page of a user on the online service are disclosed herein. In some embodiments, a computer system receives a plurality of phrases for a type of job, selects a group of phrases from the plurality of phrases based on a corresponding relevancy measurement and a corresponding diversity measurement for each phrase in the selected group of phrases, and generates a recommendation for a page of a first user based on the selected group of phrases, with the recommendation comprising a suggested addition of the selected group of phrases to the page of the first user.