Ontology-Based Information Resource Construction
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Solution Overview
Problem
Conventional methods for managing and retrieving electronic information from vast repositories, such as the World Wide Web, are inefficient due to variations in terminology and lack of effective organization, making it difficult for users to locate relevant knowledge.
Innovation Solution
A multi-user collaborative, semi-automatic system for constructing ontology-based information resources that evolves over time, using user-specified and automatically learned categorization rules, with an information management system that assists users in categorizing and storing electronic files, monitors interactions, and automatically updates categorization rules based on user interactions and search patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional keyword searching methods are used to locate information in electronic repositories, then users can access available information, but search efficiency and accuracy deteriorate due to terminology variation and lack of organization
Solution Approach 1:
The system transforms unstructured electronic information into structured ontology-based knowledge by changing the organizational parameters from simple keyword storage to hierarchical category structures with defined relationships, enabling more precise and efficient information retrieval
Solution Approach 2:
The patent introduces an intermediary processing layer (ontology construction and categorization system) between the raw electronic information and the user search interface, which mediates by standardizing terminology and organizing information into structured categories before presentation to users
2Stability of the object's composition
If manual categorization of electronic files is performed to organize information in a local electronic library, then information organization improves, but time consumption and operational complexity increase
Solution Approach 1:
The system enables self-service categorization by automatically analyzing electronic files and assigning them to appropriate ontology categories based on their content, eliminating the need for manual user intervention in the categorization process while maintaining organized information structures
Solution Approach 2:
The patent performs preliminary categorization actions by pre-processing electronic files through ontology-based classification before users need to access or search them, so that information is already organized and ready for efficient retrieval without requiring user time for categorization
3Adaptability or versatility
If static ontology categories are used to classify information, then categorization simplicity is maintained, but adaptability to new information and evolving user needs deteriorates
Solution Approach 1:
The system implements dynamic ontology categories that can automatically evolve and adapt to new information types and user needs through machine learning from user interactions, transforming the static categorization structure into a dynamic system that grows and refines itself over time
Solution Approach 2:
The patent incorporates feedback mechanisms where user interactions with the system (search patterns, categorization decisions, access behaviors) are continuously monitored and used to refine and update the ontology structure, creating a closed-loop system that adapts based on actual usage patterns
Data Source
AI summary
Systems and methods are provided for building and implementing ontology-based information resources. More specifically, multi-user collaborative, semi-automatic systems and methods are provided for constructing ontology-based information resources that are shared by a community of users, wherein ontology categories evolve over time based on categorization rules that are specified by the community of users as well as categorization rules that are automatically learned from knowledge obtained as a result of multi-user interactions and categorization decisions.