Topic Push Ranking Using Client Features for Relevance
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Solution Overview
Problem
Existing topic pushing methods have low success and effectiveness due to the subjective nature of determining topics, which are not addressed by the subjective nature of determining the relevance of the topic, leading to a low success rate and effectiveness in topic pushing.
Innovation Solution
A method and apparatus for topic pushing that involves obtaining client feature information, determining matching reference push topics, calculating ranking scores, and sending target push topics based on these scores to enhance the success rate and effectiveness by linking the push topic to a push page with associated information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If topics are manually set by operators based on subjective judgement, then the operation simplicity is maintained, but the correctness rate and success rate of topic pushing deteriorates
Solution Approach 1:
The system performs automatic topic determination through machine learning models that analyze client feature information and historical data, eliminating the need for manual operator intervention. The model independently identifies relevant topics and generates push content based on client characteristics, achieving both operational simplicity and high reliability through automated intelligent decision-making
Solution Approach 2:
The patent replaces the manual mechanical process of operator-based topic selection with an automated information processing system using machine learning algorithms. The system processes client data, identifies patterns, and determines topics automatically, substituting human subjective judgement with objective computational analysis to improve both efficiency and accuracy
2Reliability
If automatic topic determination is implemented, then the correctness rate and success rate of topic pushing is improved, but the device complexity increases
Solution Approach 1:
The machine learning model serves multiple functions: it analyzes client feature information, determines relevant topics, ranks topics by relevance, and generates push content. This multi-functional approach consolidates what would otherwise require separate systems into a single unified model, improving reliability while managing complexity through functional integration
Solution Approach 2:
The patent introduces a push topic determination model as an intermediary between raw client data and final topic selection. This intermediate processing layer transforms complex client information into structured insights that guide topic determination, making the overall system more manageable while achieving high accuracy through layered processing
3Measurement precision
If multiple ranking factors are considered for topic selection, then the topic matching precision is improved, but the calculation complexity increases
Solution Approach 1:
The system dynamically adjusts the weightings of different ranking factors based on client characteristics, historical performance data, and contextual information. By changing the parameters (weightings) rather than the number of factors, the system achieves high precision topic matching while managing computational complexity through adaptive parameter optimization rather than exhaustive multi-factor analysis
Data Source
AI summary
Embodiments of the present disclosure relate to a topic pushing processing method and apparatus, and a device and a medium. The method comprises: in response to obtaining a topic pushing request sent by a client, determining, from a current push topic pool, a plurality of reference push topics matching client feature information; according to a ranking score corresponding to each reference push topic, determining at least one target push topic from the plurality of reference push topics, and sending the at least one target push topic to the client corresponding to the topic pushing request, so that the client corresponding to the topic pushing request is controlled to display a push page of the clicked target push topic pre-constructed with a link, wherein the push page comprises associated push information of the clicked target push topic.