ML Content Query Routing for Relevant Result Presentation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional content query systems present large volumes of content in query results, leading to poor user efficiency and information integrity due to the need for users to sift through irrelevant or poorly organized content.
Innovation Solution
A method and apparatus that utilize machine learning models to determine matching degrees between user queries and query modes, extracting and presenting target content of a predetermined type in a query result page with a specific visual style, improving content retrieval efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If traditional content query systems present large volumes of content in query results, then the quantity of information provided is increased, but user efficiency and information integrity deteriorate due to the need for users to sift through irrelevant or poorly organized content
Solution Approach 1:
The patent extracts and presents only the most relevant content snippets from the query results using natural language processing and relevance scoring. Instead of displaying all content, the system extracts key information and presents it in a condensed, organized format that improves user efficiency while maintaining information integrity.
Solution Approach 2:
The patent segments large volumes of content into smaller, manageable units or snippets that are relevant to the user's query. By dividing the content and presenting only the most relevant segments in an organized manner, the system maintains quantity of information while improving user efficiency and reducing the cognitive load of sifting through irrelevant content.
2Quantity of substance
If traditional content query systems present large volumes of content in query results, then the quantity of information provided is increased, but information integrity deteriorates due to poorly organized content
Solution Approach 1:
The patent segments content into organized, relevant snippets that maintain information integrity. By dividing content into meaningful units and presenting them in a structured format with proper context, the system preserves information integrity while still providing large volumes of relevant content.
Solution Approach 2:
The patent applies local quality by organizing different portions of content with different levels of detail and formatting based on their relevance and importance. Critical information is highlighted and organized in a way that maintains integrity, while less critical information is presented in a more condensed format.
3Productivity
If machine learning models are used to determine matching degrees and extract target content, then content retrieval efficiency is improved, but device complexity increases
Solution Approach 1:
The patent uses machine learning models as intermediaries between the user's query and the content database. These models automatically determine matching degrees and extract relevant content, improving retrieval efficiency while managing complexity through automated processing rather than manual methods.
Solution Approach 2:
The system performs self-service by automatically analyzing queries, determining relevance, and extracting target content without manual intervention. The machine learning models autonomously handle the complex tasks of matching and extraction, improving efficiency while the system manages its own complexity through automated algorithms.
Data Source
AI summary
According to embodiments of the present disclosure, a solution for content query are provided. The method includes: in response to receiving a user query, determining a plurality of matching degrees between the user query and a plurality of query modes; determining, based on the plurality of matching degrees, whether a query result for the user query is to comprise a predetermined type of content being generated based on at least one data source using a machine learning model; in response to determining that the query result for the user query is to comprise the predetermined type of content, extracting target content matching with the user query from a content database comprising the predetermined type of content; and causing the target content to be presented in a query result page for the user query according to a visual style corresponding to the predetermined type.