Trend Leader Detection in Product Recommendation Systems
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Solution Overview
Problem
Conventional information processing systems fail to effectively recommend products based on purchasing behavior that creates trends, leading to insufficient promotion of sales and inability to acquire information on leading degrees of users or trend shifts using behavior history.
Innovation Solution
An information processing system with a server apparatus and output apparatus that detects trend leaders by analyzing purchase history, recommending products purchased by these leaders, and promoting sales by identifying and recommending trendy products and services.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional information processing systems are used for content recommendation, then content recommendation based on user interest and sequentiality can be achieved, but the system cannot identify trend leaders or capture trend shifts in purchasing behavior
Solution Approach 1:
The patent segments users into trend leaders and trend followers based on their purchasing behavior patterns. By dividing the user base into these distinct groups, the system can analyze and recommend products differently for each segment, capturing trend information that was previously lost in conventional unified recommendation approaches.
Solution Approach 2:
The system performs preliminary analysis of purchasing behavior to identify trend leaders before making recommendations. By pre-identifying users who exhibit trend-leading behavior (purchasing items before others), the system can proactively capture trend shifts and use this information to improve recommendation accuracy for both trend leaders and followers.
2Productivity
If purchase history information is analyzed to identify trend leaders, then product recommendation effectiveness improves, but system complexity increases
Solution Approach 1:
The system uses purchase history information that is already being collected and stored by the e-commerce platform. Instead of requiring additional external data sources or complex external analysis systems, the platform leverages its existing data infrastructure to identify trend leaders and generate recommendations, thereby improving sales promotion effectiveness without proportionally increasing system complexity.
Solution Approach 2:
The patent merges the trend leader identification function with the existing content recommendation system. By combining the analysis of purchase history patterns with the recommendation generation process, the system achieves improved productivity in sales promotion while avoiding the need for separate, complex systems. The trend leader identification is integrated into the existing architectural framework.
Data Source
AI summary
A server apparatus includes: a trend leader detecting portion that acquires purchaser identifying information for identifying a purchaser who purchased the product at an early stage satisfying a predetermined time condition, from at least two pieces of purchase history information; a recommended product acquiring portion that acquires at least one piece of product identifying information for identifying a product purchased by at least one purchaser identified with at least one piece of purchaser identifying information that has been acquired by the trend leader detecting portion; and a recommended product transmitting portion that transmits the at least one piece of product identifying information that has been acquired by the recommended product acquiring portion, to an information output apparatus. With this server apparatus, recommendation of a product can be provided based on the behavior in which a trend leader purchases a product.