Information Search Using Matching Model for Candidate Paths
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Solution Overview
Problem
Online personalized recommendation systems face challenges in accurately and efficiently recommending content to users from vast libraries, as existing methods rely heavily on historical user data, leading to insufficient precision and generalization capability.
Innovation Solution
An information search method utilizing a matching model to determine feature information of a target user, acquire candidate search paths, and filter them to recommend content by establishing a search network with tree structures and training the matching model with user operation histories to enhance search accuracy and speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional recommendation systems rely on historical user data to recommend content, then they can provide personalized recommendations, but the search precision and generalization capability are insufficient
Solution Approach 1:
The patent segments the search process into multiple candidate search paths instead of relying on a single historical-based search route. By dividing the search into multiple potential paths and evaluating them separately, the system can explore diverse recommendation possibilities while maintaining precision through systematic evaluation of each path's relevance to user features.
Solution Approach 2:
The patent changes the evaluation parameters by introducing a matching model that assesses multiple dimensions including user features, content features, and path features. This multi-parameter evaluation system improves both search precision and generalization capability by considering various factors beyond historical behavior patterns.
2Quantity of substance
If the system searches through millions of content items to provide personalized recommendations, then recommendation coverage is improved, but the search time exceeds the 500 millisecond requirement
Solution Approach 1:
The patent extracts and evaluates only the most promising candidate search paths from the vast content library rather than searching through all millions of items. By identifying and focusing on a limited number of high-potential paths based on initial matching criteria, the system achieves comprehensive coverage of relevant content while completing the search within the 500 millisecond time constraint.
Solution Approach 2:
The patent performs preliminary evaluation of candidate search paths before full content retrieval. By pre-assessing paths based on user features and content metadata, the system filters out unpromising paths early in the process, allowing comprehensive content coverage to be achieved through focused search on only the most relevant paths within the time limit.
3Measurement precision
If the system uses multiple candidate search paths to improve recommendation accuracy, then search precision is improved, but the system complexity increases
Solution Approach 1:
The patent implements a dynamic system where the number and selection of candidate search paths adjust based on user features and context. Rather than always evaluating a fixed large number of paths, the system dynamically determines the appropriate level of path exploration, balancing recommendation accuracy with computational complexity through adaptive path selection and evaluation.
Data Source
AI summary
An information search method and apparatus, a device and a storage medium, relating to fields of intelligent search, intelligent recommendation, deep learning and the like. A specific implementation includes: determining feature information of a target user; acquiring at least one candidate search path to determine candidate search results in a database; determining a matching degree between the feature information of the target user and the at least one candidate search path using a matching model, and determining a target search path from the candidate search paths according to the matching degree; and determining a target search result matched with the target user using the target search path.