Personalized Shopping Recommendation System Using User-Built Categories
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Solution Overview
Problem
Online shopping faces challenges as users often struggle to identify and search for specific item attributes, leading to inefficient browsing across multiple platforms without knowing exactly what they are looking for.
Innovation Solution
A system and method that allow users to create and manage user-built categories, analyze selected attributes from text and images, and recommend items based on aggregated user preferences, using a browser plugin or extension to facilitate personalized shopping experiences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users manually browse through multiple shopping platforms to find items with specific attributes, then they can find items matching their preferences, but the time and effort required increases significantly
Solution Approach 1:
The system performs preliminary analysis of item attributes and user preferences before the actual shopping search. By pre-processing and organizing attribute data from multiple platforms, the system prepares the information in advance so that users can quickly find matching items without manually browsing through each platform.
Solution Approach 2:
The patent introduces an intermediary system that acts as a bridge between multiple shopping platforms and users. This intermediary automatically collects, analyzes, and aggregates item attributes from various platforms, then presents them in a unified interface, eliminating the need for users to manually search across multiple platforms.
2Adaptability or versatility
If users search for specific item attributes without knowing exactly what they are looking for, then they can discover new items, but the search efficiency decreases
Solution Approach 1:
The system implements feedback mechanisms that learn from user interactions and browsing behavior. By analyzing which attributes users view, compare, or select, the system provides intelligent suggestions and refines search results in real-time, helping users discover relevant items while maintaining search efficiency.
Solution Approach 2:
The search system is designed to be dynamic and adaptive, automatically adjusting search parameters and presenting results based on user behavior patterns. The system can shift between exploratory mode (for discovery) and targeted mode (for efficiency) based on real-time user interactions.
3Loss of information
If users manually analyze and compare item attributes across different platforms, then they can make informed decisions, but the complexity of the process increases
Solution Approach 1:
The patent merges attribute information from multiple shopping platforms into a unified comparison interface. By consolidating data from different sources and standardizing the presentation format, the system enables users to compare items across platforms without manually collecting and organizing information from each source separately.
Solution Approach 2:
The system segments the complex attribute comparison process into manageable components. It categorizes attributes into relevant groups, highlights key differences between items, and presents information in structured formats that reduce cognitive load while maintaining completeness.
Data Source
AI summary
A system and method for personalizing user interest based on user built profiles are provided. In example embodiments, the system may include a non-transitory, computer-readable medium storing computer-executable instructions and one or more processors. When the one or more processors execute the computer-executable instructions, the processors may be configured to receive a first attribute and a second attribute describing an item of interest submitted by a user, the first attribute and the second attribute assigned to a category by the user. When the first attribute is received, the one or more processors may determine at least one shared feature between the first attribute and the second attribute, and display recommended items to the user that include the at least one shared feature.