Interest Vector Recommendation Matching for User-Item-Shop Alignment
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Solution Overview
Problem
Existing recommendation systems fail to accurately reflect user interests and concerns in product or service recommendations.
Innovation Solution
A recommendation system comprising a client device and server device that form interest information vectors, calculate distances between user, item, and shop information, and provide recommendations based on predefined conditions, using a client and server program to determine and present relevant information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If recommendation is provided based on image only, then the system is simple to operate, but the recommendation cannot appropriately reflect user interest or concern
Solution Approach 1:
The patent combines multiple data sources (image data, user profile data, item data, shop data) into a unified recommendation system. The interest information formation unit creates comprehensive interest information by integrating these diverse data types, allowing the system to maintain ease of operation while significantly improving measurement precision of user interests through multi-dimensional data analysis.
Solution Approach 2:
The recommendation system is designed with multi-functionality to handle various data types and provide comprehensive recommendations. The server device performs multiple functions including image processing, user profile analysis, item matching, and shop recommendation, enabling the system to accurately reflect user interests through diverse data processing capabilities.
2Measurement precision
If multiple types of information are collected and processed, then the recommendation accuracy is improved, but the device complexity increases
Solution Approach 1:
The patent segments the complex recommendation system into distinct functional units: interest information formation unit, distance calculation unit, and recommendation determination unit. Each unit handles specific tasks (image processing, data integration, distance calculation, recommendation selection), which simplifies the overall system architecture while maintaining high measurement precision through specialized processing at each segment.
Solution Approach 2:
The patent introduces an intermediary interest information vector space that mediates between raw data inputs and final recommendations. By transforming diverse data types into a unified interest information representation, the system simplifies the complexity of processing multiple information types while maintaining accurate user interest measurement through the distance calculation in this intermediate space.
Data Source
AI summary
A server device includes: an interest information formation unit for forming interest information which is a vector obtained by digitizing a plurality of adjectives expressing a user, item information, and shop information; a distance calculator for calculating a first distance between the interest information for the user and the interest information on the item information, and a second distance between the interest information for the user and the interest information on the shop information; a recommendation information determination unit for determining that if the first distance and the second distance meet prescribed conditions, the item information corresponding to the first distance and the shop information corresponding to the second distance are recommendation information to be recommended to the user; and a recommendation information provision unit for providing a client device with the recommendation information.