Automated Metadata Classification for Content Servers

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Solution Overview

Problem

Content management systems like OpenText Content Server lack an efficient method to understand and categorize documents based on their content, making it difficult to update metadata automatically, especially when documents are spread across the system.

Innovation Solution

The system integrates the Shinydocs Cognitive Suite to crawl and extract metadata from documents, assign attributes, and synchronize these attributes back into the content management system, utilizing automated methods to classify and reorganize documents efficiently.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If manual classification of documents is performed in Content Server, then metadata can be updated, but the process is extremely time-consuming and inefficient

Engineering Contradiction:

Improvedocument classification speedVSAvoidtime to classify documents

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The patent replaces manual mechanical classification processes with automated cognitive technology. The Shinydocs Cognitive Suite uses AI and machine learning to automatically analyze document content, extract metadata, and classify documents, substituting human manual effort with automated intelligent systems that process documents much faster and at scale.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent introduces an intermediary system (Shinydocs Cognitive Suite) that bridges Content Server and automated classification capabilities. This intermediary component crawls documents, extracts content, generates metadata, and updates Content Server automatically, serving as a mediator between the content management system and the classification process.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Extent of automation

If automated classification tools are integrated, then document understanding and metadata updating improve, but system complexity increases

Engineering Contradiction:

Improveautomated document classificationVSAvoidsystem architecture complexity

Core Design Contradiction:

Extent of automationVSDevice complexity

Solution Approach 1:

The patent implements a universal classification system that handles multiple document types, formats, and classification criteria through a single integrated platform. The Shinydocs Cognitive Suite provides multi-functional capabilities including document crawling, content extraction, metadata generation, and classification across diverse document formats, reducing the need for separate specialized tools.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The system enables self-service automated classification where the Cognitive Suite independently crawls documents, analyzes content, generates appropriate metadata, and updates Content Server without requiring manual intervention. The system serves itself by automatically managing the entire classification workflow from document discovery to metadata implementation.

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS12141213B2System and method of updating content server metadata

Publication Date: 2024.11.12 SHINYDOCS

AI summary

A system and method of updating Content Server metadata on order to update and re-organize documents in a content management system (i.e., Content Server). A content management system includes a tool for setting Content Server metadata attributes, based in values in the index. Content Server Category Attributes can be set, as can Content Server Classification values, as can Content Server RM Classification values.