Multi-Level Advertisement Information Store for Product Diversity
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Solution Overview
Problem
Conventional Internet advertising systems are limited in product range and diversity, leading to ineffective advertisements with low click-through rates, wasting server and network resources due to the inability to adequately cover various product categories.
Innovation Solution
A multi-level advertisement information store organizes advertisement information into categories, using query keywords to select candidate advertisements based on correlation values, ensuring product-category diversity by selecting a preset number of advertisements from each category, and weighting them for relevance and user response history.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If basic query keyword matching is used to select advertisements, then the advertisement placement process is simple and fast, but the product range and diversity are limited
Solution Approach 1:
The advertisement database is segmented into multiple category levels (first-level categories, second-level categories, and third-level categories). This segmentation allows the system to retrieve advertisements from specific category levels based on query keywords, enabling diverse product range while maintaining simple keyword matching operation. The segmentation principle resolves the contradiction by organizing data structure rather than changing the query process.
Solution Approach 2:
The system adds a category level dimension to the traditional keyword matching approach. Instead of only matching keywords against a flat advertisement database, the system now operates in a multi-dimensional space where advertisements are organized by category levels. This dimensional change enables diverse product coverage while maintaining the simplicity of keyword-based retrieval.
2Productivity
If conventional keyword matching is used, then the system is simple and efficient, but click-through rate is low and server resources are wasted
Solution Approach 1:
The system performs preliminary organization of advertisements into multi-level category structures before receiving queries. This preliminary action allows the system to efficiently retrieve and rank advertisements by category relevance when queries arrive, improving both efficiency and effectiveness. The pre-organized category structure enables fast processing while ensuring high-quality advertisement selection.
Solution Approach 2:
The system uses feedback from user interactions and advertisement performance data to refine future advertisement selections. By analyzing which advertisements achieve high click-through rates and which categories perform best, the system can optimize its keyword matching and category-based retrieval processes, improving overall effectiveness while maintaining efficiency.
Data Source
AI summary
Advertisement placement includes: obtaining one or more advertisement query keywords; determining, using one or more computer processors, in a multi-level advertisement information store, a selection of advertisement information for placement; and presenting the selection of advertisement information to be placed at a client. The multi-level advertisement information store comprises advertisement information organized into a plurality of first-level categories, and each first-level category is associated with a respective plurality of subordinate levels of categories.