Search Result Sorting via Type-Style Scoring
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current search systems face challenges in effectively sorting search results to meet user requirements and push relevant information, as they struggle to accurately prioritize results based on user preferences and commercial value.
Innovation Solution
A method for sorting search results that involves acquiring initial search results, determining the type and style of each result, assigning scores based on a preset mapping relationship, and adjusting the order of results to prioritize those with higher scores, thereby enhancing the relevance and commercial value of the sorted results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If search results are sorted based on traditional relevance algorithms, then search accuracy is improved, but the ability to push commercial value and meet user preferences is insufficient
Solution Approach 1:
The patent changes the sorting parameters from traditional relevance-based metrics to a dual-dimensional scoring system that includes both relevance scores and commercial value scores. This allows the search system to simultaneously optimize for search accuracy and information pushing capability by adjusting the weightings and thresholds of these parameters.
Solution Approach 2:
The patent segments the search result evaluation into distinct components: relevance evaluation and commercial value evaluation. Each component is assessed independently using specific algorithms and criteria, then combined to produce the final sorted order. This segmentation enables optimized handling of each aspect without compromising the other.
2Productivity
If search results are sorted to prioritize commercial value, then information pushing is improved, but user search requirements may not be fully satisfied
Solution Approach 1:
The patent implements a dynamic sorting mechanism that adjusts the balance between relevance and commercial value based on user behavior patterns and search context. The system dynamically weights the two scoring dimensions to ensure both information pushing efficiency and user requirement satisfaction are achieved simultaneously.
Solution Approach 2:
The system incorporates feedback loops that monitor user interactions with search results and adjust the sorting algorithm accordingly. This feedback mechanism ensures that commercial value pushing does not compromise user satisfaction, as the system learns from user behavior and refines its sorting decisions in real-time.
3Measurement precision
If a complex scoring system is introduced to evaluate type and style, then sorting precision is improved, but system complexity increases
Solution Approach 1:
The patent segments the complex evaluation process into distinct modules: type evaluation, style evaluation, relevance scoring, and commercial value scoring. Each module handles a specific aspect of the evaluation independently, making the overall complex system more manageable and maintainable while achieving high sorting precision through the combination of these segmented functions.
Data Source
AI summary
A method for sorting search results, includes: acquiring a plurality of first search results corresponding to a search request and an initial order of the plurality of first search results; determining a type and a style of each of at least one first search result in response to the at least one first search result being push information; based on a preset mapping relationship, determining a first score corresponding to each of the at least one first search result according to the type and the style of each of the at least one first search result; and acquiring an updated order of the plurality of first search results by adjusting the initial order in order of the first score from largest to smallest.