Personalized Document Aggregation System for Digital Rights Management
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Solution Overview
Problem
Digital rights management systems do not effectively help users, particularly students, in organizing and managing multiple digital documents for educational purposes, lacking tools for convenient aggregation and association of content based on user interactions.
Innovation Solution
A method and system that aggregates content from multiple digital documents into personalized, aggregated documents and creates associations among them based on user interactions, using a server and client computer setup to collect and analyze interaction data, generate content importance scores, and display related documents with link icons for easy navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If users access multiple digital documents for study, then they can access comprehensive course materials, but it becomes difficult to organize and manage the documents efficiently
Solution Approach 1:
The system merges multiple digital documents into an aggregated document that combines contents from original documents based on user interactions. The aggregated document integrates information from multiple sources while maintaining individual document access, thereby reducing the complexity of managing multiple separate documents.
Solution Approach 2:
The system introduces an intermediary layer between the user and multiple documents by creating an aggregated document that serves as a unified interface. This intermediary structure organizes and presents document contents in a coordinated manner, making document management more efficient without losing access to original materials.
2Adaptability or versatility
If users manually organize multiple documents, then they can create personalized study packages, but it consumes significant time and effort
Solution Approach 1:
The system performs self-service by automatically analyzing user interactions with documents and generating aggregated documents without manual intervention. The system monitors user behavior patterns, identifies relevant content, and creates personalized document packages autonomously, eliminating the need for users to manually organize materials.
Solution Approach 2:
The system performs preliminary action by pre-processing user interaction data and pre-generating aggregated documents before users need to review materials. By continuously monitoring and analyzing interactions, the system prepares personalized document packages in advance, saving users time when they need to access study materials.
3Reliability
If users review multiple documents separately, then they can access complete information, but it reduces review efficiency and increases time consumption
Solution Approach 1:
The system combines multiple documents into an aggregated document that preserves complete information from original sources while enabling more efficient review. The aggregated structure maintains links to original documents, ensuring information completeness while allowing users to review consolidated content in a single interface.
Solution Approach 2:
The system segments the review process into two levels: the aggregated document provides a consolidated overview for efficient review, while individual original documents remain accessible for detailed examination. This segmentation allows users to navigate between summary and detail views, improving review efficiency without sacrificing information completeness.
Data Source
AI summary
Methods for managing contents of multiple digital documents for individual users, to generate aggregated documents from multiple documents and/or create associations among multiple documents, based on the user's interactions with multiple digital documents. A document content aggregation method can, on a personalized basis, aggregate contents from multiple digital documents into an aggregated document based on a user's past interactions with the documents. The aggregation is based on a content importance score calculated from the user interaction pattern. A document association method can, on a personalized basis, create associations among multiple digital documents based on the user's past interactions with the documents. Two documents are deemed related if there is a user interaction pattern where the user interacts with both documents with a predetermined time interval from each other. When displaying one document, link icons are displayed to allow the user to directly navigate to the related documents.