Vertical Search Query System Category Ranking Optimization
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Solution Overview
Problem
Current e-commerce websites face challenges with vertical search engines, including low relevance of categories presented to users, lack of relative importance indication between categories, and categories of high importance being inadvertently hidden due to threshold settings, leading to overwhelming commodity classification information.
Innovation Solution
A method and system for vertical search-based queries that involve receiving user queries, generating category models from user interactions, combining query results from category and commodity warehouses, and updating models based on user clicks to enhance relevance and importance ranking of categories.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If a threshold is set to hide categories with low result counts, then the amount of classification information is reduced, but categories of high importance may be inadvertently hidden
Solution Approach 1:
The patent changes the parameter used for category ranking from result count to a comprehensive scoring mechanism that incorporates multiple factors including user interaction data, category importance weights, and relevance metrics. This allows important categories to be displayed even when they have fewer results, resolving the contradiction between reducing information overload and maintaining category importance indication.
2Manufacturing precision
If manual entry and maintenance of commodity data is done, then data accuracy is maintained, but the complexity of data management increases
Solution Approach 1:
The patent implements automated data extraction and classification systems that self-update commodity information from multiple sources. The system automatically parses product data, categorizes items, and maintains the commodity database without requiring manual intervention, thereby maintaining data accuracy while significantly reducing management complexity.
3Measurement precision
If comprehensive category models are generated from user interactions, then search result relevance is improved, but the time required for model processing increases
Solution Approach 1:
The patent pre-generates and caches category models based on historical user interaction data during off-peak periods. When users perform searches, the system retrieves pre-computed models rather than generating them in real-time, thus maintaining high relevance while minimizing processing time. The system also implements incremental updates to models based on new interaction data.
Data Source
AI summary
Various embodiments of a method, system, and apparatus related to query based on vertical search are disclosed. In one aspect, a method of query based on vertical search receives a user query. The method obtains a first category model from a category model warehouse based on the user query to generate a first query result. The first category model includes one or more commodity categories that correspond to one or more keywords in the user query. The method also obtains one or more commodity categories corresponding to the user query from a commodity warehouse to generate a second query result. The method further generates a final query result by combining the first query result and the second query result.