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Inference Tagging

Bringing hidden knowledge to the surface.
Inference Tagging

Inference tagging makes it possible to annotate documents beyond explicit concepts by deriving new information from implicit concepts. Rather than having to collect additional data to extract tags, inference tagging leverages the existing dataset to generate new knowledge and connections.

Inference tagging is built on ontologies and rules. Where ontologies define the structural model of the data, including classes and subclasses, rules establish the laws that the data must adhere to. By utilizing these tools, inference tagging can reveal hidden relationships within the data, leading to valuable insights and connections that might have been previously unnoticed.

With inference tagging you can interpret the data, draw conclusions, and make predictions. It is a critical component in many automated decision-making processes, as it helps computers understand complex patterns and relationships within data.

Identify the hidden knowledge in your documents!

There are various methods for bringing hidden knowledge to the surface. With inference tagging, you can create metadata that reveals information and conclusions that would otherwise remain hidden in your documents.

Implicit tagging

Inference Tagging is a powerful approach to analyse and annotate large collections of documents, particularly in scenarios where explicit labels or categories are not available or are inconsistent.

Scenario-based tagging

With inference tagging, the combination of concept tagging and annotation rules allows the flexible classification of documents according to changing readings or scenarios.

Multi-domain tagging

Even very different branches of a taxonomy can be used with flexible rules to annotate documents and allow multiple classifications in different domains.

Conditional tagging

Applying rules to the extracted facts allows documents to be tagged based on recognized patterns and keywords.


Example use cases

Inference Tagging is used in a wide range of applications.

Risk identification

To analyze and annotate reports, procedures, and statements, etc., inference tagging lets you associate risk types and risk levels to the concepts detected in the text. In the healthcare domain, for example, the application of inference tagging to patient data can facilitate the prognostication of health risks, the identification of preventative strategies, and the elucidation of potential therapy interventions.

Pattern detection

With inference tagging, you are able to act on occurence patterns of the concepts in a document or even their structural relationship. You can produce signals which may trigger a certain classification of the document and warnings, alarms or actions.

In manufacturing, this may be signals to review a process or start maintenance derived from shift reports.

Personalized recommendations

The flexible classification of documents according to changing readings or scenarios can be realized in modeling user behaviour and user preferences in the inference rule.

In the area of personal recommendation systems – e.g. in commerce, retail or self service – this enables recommendation systems that take context, user intent and user behavior into account.

Decision support

A document that has been enriched with implicit concepts and facts using inference tagging makes it possible to link further background information that is already focused on the scope of the decision.

A patient’s medical history can thus support doctors in treatment by providing links to diagnostic suggestions based on the symptoms entered by the healthcare provider.

Useful Resources

Inference Tagging Demo

Watch the chapter about Inference Tagging in our Webinar “What’s New: PoolParty Recommender”

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Tagging 101

Learn  more about Concept Tagging and how  you can benefit from precise automated tagging and classification

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Inference Tagging Workbench

Have a look into our documentation of our Workbench to see how PoolParty supports you in drafting your inferencing rules.

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Want to explore these applications yourself? Reach out to us to learn more about Inference Tagging from an expert.