Distributed Resource Tagging and Semi-Automatic Categorization
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Solution Overview
Problem
Current systems lack efficient methods for categorizing and retrieving software components in distributed applications, which hinders the rapid location and substitution of suitable components, and does not leverage tagging techniques effectively.
Innovation Solution
A distributed system that automatically organizes digital resources using keywords, allowing users to modify these groups, and utilizes the modified taxonomy for efficient retrieval of digital resources, including documents and software components, by employing a service browser with tagging and semi-automatic categorization processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If digital resources are manually categorized using hierarchical folder systems, then users can navigate to resources through structured paths, but the time required to locate specific resources increases significantly
Solution Approach 1:
The patent segments the categorization process into two independent dimensions: automatic keyword-based grouping and manual hierarchical folder structure. This allows resources to be organized by multiple keywords simultaneously without requiring deep nested folder paths, enabling direct retrieval through keyword matching while preserving user-controlled hierarchical navigation.
Solution Approach 2:
The patent introduces an intermediary automatic categorization system that generates keyword groups independently of the manual folder hierarchy. This intermediary layer acts as a mediator between unstructured resources and user queries, providing rapid retrieval paths through automatically extracted keywords while the folder structure remains for user-defined organization.
2Productivity
If automatic keyword-based grouping is implemented without user control, then retrieval speed improves, but users cannot modify or refine the categorization to match their specific needs
Solution Approach 1:
The patent merges automatic keyword-based grouping with manual hierarchical folder structures into a unified retrieval system. Both categorization approaches coexist and can be used together: the automatic grouping provides rapid initial retrieval through keyword matching, while users can refine results using their personal folder hierarchies and apply additional filters based on their specific needs.
Solution Approach 2:
The patent creates a dynamic categorization system where the classification structure can adapt to different user needs. Users can dynamically switch between viewing resources by automatic keyword groups or by their personal folder hierarchies, and can combine both approaches in hybrid query strategies depending on the retrieval task at hand.
3Measurement precision
If comprehensive tagging of all digital resources is performed, then retrieval precision improves, but the complexity of managing and maintaining tags increases
Solution Approach 1:
The patent implements self-service automatic tag generation using natural language processing and text analysis algorithms. The system automatically extracts relevant keywords from resource content, metadata, and descriptions without requiring manual tagging by users. This automated approach achieves comprehensive tagging coverage while eliminating the manual labor and complexity of maintaining extensive tag systems.
Solution Approach 2:
The patent replaces the manual mechanical process of tag assignment with automated computational methods. Natural language processing algorithms, text mining techniques, and machine learning models substitute for human users manually assigning tags, thereby achieving comprehensive and precise tagging at scale without the operational complexity of manual tag management.
4Stability of the object's composition
If users must drill through multiple hierarchical folders to find resources, then organization structure is maintained, but the number of navigation steps increases
Solution Approach 1:
The patent adds another dimension to resource organization by implementing parallel keyword-based grouping alongside the traditional hierarchical folder structure. Instead of requiring users to navigate through multiple folder levels (vertical dimension), users can directly access resources through keyword-based flat grouping (horizontal dimension), effectively adding a new organizational dimension that bypasses deep navigation paths while preserving folder structure integrity.
Data Source
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AI summary
The present invention relates to distributed systems in which resource utilisation decisions depend upon the semi-automatic categorisation of resource descriptions stored in the distributed system. In the principal embodiment, the resource descriptions are web service descriptions which are augmented with tags (i.e. descriptive words or phrases) entered by users and/or by web service administrators. The initial use of automatic categorisation of these descriptions, followed by a user-driven fine-tuning of the automatically-generated categories enables the rapid creation of reliable categorisation of the resource descriptions, which in turns results in better resource utilisation decisions and hence a more efficient use of the resources of the distributed system.