User Trainable Interface Page Classification System
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Solution Overview
Problem
Users face challenges in automatically classifying and retrieving information from user interface pages, such as product pages, without actively bookmarking or saving links, especially when encountering unknown merchant websites or schemas.
Innovation Solution
A user trainable user interface page classification system that applies a rule set to identify and extract attributes from user interface pages, allowing users to train the system to recognize unknown merchant pages by identifying elements like price, name, and image, and generating domain cards for later reference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the system automatically classifies user interface pages using a rule set, then classification efficiency is improved, but accuracy deteriorates when encountering unknown merchant websites or schemas
Solution Approach 1:
The system implements feedback by allowing users to provide corrections when automatic classification fails. Users can manually classify pages and the system learns from these corrections by updating the rule set, creating a closed-loop feedback mechanism that continuously improves accuracy while maintaining automated efficiency
Solution Approach 2:
The system performs preliminary classification using the rule set before user intervention is needed. This preliminary action handles the majority of cases automatically, and only requires user input when the preliminary classification is incorrect or uncertain, thus maintaining efficiency while improving accuracy
2Loss of information
If users actively bookmark and save links to keep track of visited pages, then information retrieval capability is improved, but user operation complexity increases
Solution Approach 1:
The system performs self-service by automatically classifying and organizing visited pages without requiring user actions. The system autonomously applies the rule set to categorize pages, extracts relevant information, and maintains the classification structure, freeing users from manual bookmarking while preserving full information retrieval capability
Solution Approach 2:
The system acts as an intermediary between the user and the information management process. It mediates by automatically handling the classification and organization tasks that would otherwise require direct user action, while still providing users with access to organized information when needed
Data Source
AI summary
A user trainable user interface page classification system applies a rule set to information associated with a user interface page to determine whether the user interface page satisfies a domain page condition. If the user interface page does not satisfy the domain page condition, a user trains the system such that the user interface page classification system classifies the user interface page as a domain page. The rule set of the user interface page classification system is updated, and the updated rule set is applied to the information associated with the user interface page. The user interface page classification system then classifies the user interface page as a domain page.