Phrase Placement Classifier 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, and users face difficulties in efficiently adding necessary data to their pages.
Innovation Solution
A computer system identifies job postings relevant to a user's interests and extracts key phrases, using a placement classifier to suggest their placement on the user's page, allowing for convenient and efficient addition of these phrases 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 increases
Solution Approach 1:
The system automatically extracts phrases from job postings and places them on user profiles without requiring manual user input. The automated system serves itself by identifying relevant data, extracting key phrases, and positioning them appropriately on user pages, eliminating the need for users to manually add this information while maintaining high accuracy in search results
Solution Approach 2:
The system performs preliminary actions by proactively identifying and extracting relevant phrases from job postings before users need them for search optimization. By anticipating what data users will need and preparing it in advance, the system eliminates the time users would otherwise spend manually gathering and adding this information
2Loss of information
If users spend more time searching for relevant data, then they can find more complete information, but electronic resources such as network bandwidth and computational expense increase
Solution Approach 1:
The system performs preliminary data preparation by automatically populating user profiles with relevant phrases from job postings before searches are executed. This pre-positioning of relevant data eliminates the need for users to conduct extended searches and reduces redundant computational operations during search execution, thereby decreasing electronic resource consumption while maintaining information completeness
Solution Approach 2:
The system uses feedback from job posting data to continuously optimize user profiles. By monitoring what phrases appear in relevant job postings and automatically incorporating them into user pages, the system creates a self-improving mechanism that enhances search completeness without requiring additional computational resources during actual search operations
3Ease of operation
If a placement classifier is used to suggest phrase placement, then the ease of adding data to pages improves, but the device complexity increases
Solution Approach 1:
The placement classifier operates autonomously without requiring user configuration or intervention. It automatically analyzes job posting data, determines appropriate placement locations on user profiles, and positions phrases accordingly. This self-service capability provides users with an easy-to-use system that handles the complexity internally while presenting a simple interface
Solution Approach 2:
The placement classifier acts as an intermediary between job posting data and user profiles. It translates raw job posting information into appropriately positioned phrases on user pages, mediating the complex processing requirements while presenting a simple outcome to users. This intermediary layer encapsulates the complexity, allowing users to benefit from sophisticated phrase placement without understanding or managing the underlying complexity
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, and then, for each one of the plurality of phrases, selects a corresponding section of a page of a first user to suggest for placement of the phrase from amongst a plurality of sections using a placement classifier, and generates a corresponding recommendation for the page of a first user based on the phrase and the determined corresponding section of the page of the first user, with the recommendation comprising a suggested addition of the phrase to the determined corresponding section of the page of the first user.