Knowledge Graph Auto-Filing for Unlinked ECM Documents

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Solution Overview

Problem

Existing enterprise content management systems struggle with limited interoperability between unstructured content and structured data, leading to manual and inefficient filing of content objects to workspaces, especially when there is no prior relationship to a business object.

Innovation Solution

Implementing an intelligent auto filing system based on entity linking, which detects indicators in documents, queries a knowledge graph to identify relevant workspaces, and classifies documents for automatic filing, even without prior connections to business objects.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If manual filing processes are used for content objects without prior relationships to business objects, then flexibility and adaptability are maintained, but productivity and efficiency deteriorate due to high manual effort

Engineering Contradiction:

Improveability to file documents without prior relationshipsVSAvoidfiling efficiency

Core Design Contradiction:

Adaptability or versatilityVSProductivity

Solution Approach 1:

The system enables documents to automatically file themselves to appropriate workspaces through entity linking technology. The auto-filing system detects entities in documents, queries the knowledge graph, and autonomously determines the correct workspace without human intervention, transforming manual filing into a self-service automated process

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces manual mechanical filing operations with an automated intelligent system. Entity linking technology and knowledge graph querying substitute human cognitive and manual actions, automating the document routing process while maintaining adaptability to various document types and relationships

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Productivity

If automated filing systems are implemented, then productivity and efficiency improve, but device complexity and system requirements worsen due to knowledge graphs and entity linking

Engineering Contradiction:

Improveautomated filing efficiencyVSAvoidsystem architecture complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The knowledge graph serves multiple functions: storing entity relationships, enabling entity linking, supporting document classification, and facilitating workspace determination. This multi-functional component reduces overall system complexity by consolidating what would otherwise require separate systems for each function

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The knowledge graph acts as an intermediary layer between documents and workspaces. Instead of direct complex mappings, the system uses entity linking through the knowledge graph as a mediator, simplifying the architecture by introducing a standardized intermediate representation layer

Inventive Principle:

Principle #24Intermediary (Mediator)

3Adaptability or versatility

If entity linking is used for documents not well named for natural language processing, then adaptability improves, but measurement precision and detection accuracy worsen

Engineering Contradiction:

Improveability to process various document typesVSAvoidentity detection accuracy

Core Design Contradiction:

Adaptability or versatilityVSMeasurement precision

Solution Approach 1:

The system extracts multiple potential entity indicators from documents, even if some are not perfectly named or formatted. By extracting more indicators than strictly necessary and using scoring mechanisms to evaluate candidate workspaces, the system compensates for imperfect entity naming while maintaining acceptable accuracy

Inventive Principle:

Principle #16Partial or excessive action

Solution Approach 2:

The entity linking process uses feedback from knowledge graph queries and scoring mechanisms to refine entity detection. The system evaluates candidate workspaces based on extracted indicators, learns from matching patterns, and adjusts entity detection strategies to improve accuracy for various document types over time

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS20260010517A1Systems and methods for intelligent automatic filing of documents in a content management system

Publication Date: 2026.01.08 OPEN TEXT SA ULC

AI summary

Embodiments provide for intelligent auto filing of documents to enterprise content management (ECM) system workspaces. Embodiments may include maintaining a database of ECM information including a plurality of enterprise workspaces having attributes; based on the ECM information, generating a knowledge graph comprising nodes for enterprise workspaces and edges for relationships between enterprise workspaces; receiving a document for filing in one of the enterprise workspaces; detecting a plurality of indicators in the document text and evaluating the indicators to generate a subset of strong indicators in the plurality of indicators; querying the knowledge graph based on the strong indicators to generate a set of candidate enterprise workspaces; comparing the set of candidate enterprise workspace attributes to the strong indicators to determine a score of each candidate enterprise workspace; and based on the scores, linking and storing the document to one of the candidate enterprise workspaces.