Information Pushing Method Using Keyword Matching
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Solution Overview
Problem
Commercial customers face challenges in achieving high-quality traffic and conversion efficiency for their advertisements due to low-quality document content and the inability to automatically determine suitable content or format for marketing components, leading to suboptimal exposure and conversion effects.
Innovation Solution
A method that predicts the effective rate of information pushing on initial pages based on document content, selects candidate pages, extracts keywords, and determines target pages for information mounting using a matching degree between keywords, thereby optimizing advertisement placement and reducing manual workload.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual selection of pages for advertisement mounting is performed, then advertisement placement accuracy can be ensured, but workload and time consumption increase significantly
Solution Approach 1:
The system performs self-service by automatically evaluating pages and selecting candidate pages for advertisement mounting without human intervention. The server autonomously calculates effective rates, extracts keywords, and determines target pages based on matching degrees, eliminating the need for manual page selection while maintaining high placement accuracy
Solution Approach 2:
The manual mechanical process of page selection is replaced with an automated information processing system. The server uses algorithms to predict effective rates, extract keywords, and calculate matching degrees, substituting human manual evaluation with computational automation that achieves both accuracy and efficiency
2Productivity
If random pages are selected for advertisement mounting, then workload is reduced, but exposure rate and conversion efficiency decrease
Solution Approach 1:
The system uses feedback mechanisms by calculating effective rates based on document content quality and user interaction data. Pages are evaluated and ranked according to their predicted effectiveness for advertisement mounting, ensuring that selected pages have high exposure potential while reducing manual workload
Solution Approach 2:
The system changes the parameter of page selection from random to systematic evaluation based on multiple parameters including effective rate, keyword matching degree, and document content quality. This systematic approach ensures high exposure rates while automating the selection process
3Measurement precision
If keyword matching is performed for all pages, then advertisement relevance improves, but system complexity and processing time increase
Solution Approach 1:
The system segments the page selection process into distinct stages: first evaluating effective rates based on document content, then extracting keywords from candidate pages, and finally performing keyword matching. This segmentation reduces overall complexity by processing only a subset of pages in detail rather than all pages simultaneously
Solution Approach 2:
The system performs preliminary evaluation of effective rates before conducting keyword matching. Pages are pre-screened based on their document content quality and predicted effectiveness, so that keyword matching is only performed on a reduced set of candidate pages, reducing processing complexity while maintaining relevance
Data Source
AI summary
A method for pushing information, and an electronic device are disclosed. The method includes: obtaining a plurality of initial pages containing document content; predicting, based on the document content in the plurality of initial pages, an effective rate for pushing information using each initial page; selecting, based on the effective rate, at least one candidate page from the plurality of initial pages and extracting a first keyword from the document content of the at least one candidate page; and determining a target page for mounting information to be pushed from the at least one candidate page, based on a matching degree between a second keyword of the information to be pushed and the first keyword.