CONVERSION

XML conversion of research papers 

for improved discoverability.

Well-structured content and granular data structures are critical for content discovery and monetisation.

Conversion streamlines the structure and precision of the digital representation of a research paper, elevating content usability and discoverability. With an advanced AI/ML-based engine trained on millions of research articles, a universal DTD that covers all possible structural nuances, and using error awareness to guide human involvement, we produce XML files with the highest element-level precision.

What sets us apart

Artificial intelligence

A unique, best-in-class ML model that presents 99.97% accuracy with built-in error awareness
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Error awareness

A bespoke schema and schematron engine that works in tandem with an ML model to accurately identify errors that need human intervention
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Continuous improvement

A robust data pipeline with granular visualisation, allowing product teams to continuously improve the efficacy of the technology and human intervention

Maximum coverage

A universal DTD developed over years that covers all possible elements and structures
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User experience

A browser-based structuring platform built to be user-friendly and can be used by anyone, even without XML expertise

Coming soon to conversion

Microservices

A modular and dynamic approach to article processing, allowing individual modules to be triggered seamlessly throughout the content generation pipeline. With this system in place, each component of an article, such as front matter, references, and tables, can initiate specific microservices tailored to its processing requirements.

XML Central

XML Central will streamline the conversion process, ensuring accuracy and efficiency in transitioning manuscripts from Word documents to publisher-ready XML files. It will serve as a pivotal platform where accepted Word manuscripts can be ingested, initiating a process where tools equipped with error detection capabilities are employed. The system automatically extracts the information and structure required by publishers, generating an XML file ready for publication without manual intervention.

Tiered conversion models

By enabling simple, medium, and complex tiers, the system can adapt its conversion methods according to the metadata and submission patterns of the documents being processed.

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