Challenges
Manual indexing is slow and expensive as finding the relevant indexing terms is a time-consuming task and in the case of full-text of articles, it could be overwhelming. On the other hand, automated document indexing is faster, more reliable, and cost-effective compared to manual indexing.
Approach
Straive offers an automated deep indexing solution that leverages cutting-edge analytics and data science methodologies to classify even unstructured documents using the extreme multilabel classification (XMLC) method.
Deep indexing by extreme multilabel classification is a highly efficient methodology for indexing:
- Enhancing functionality
- Expanding readership
- Upholding accessibility regulations
Impact
Learn how Straive used the extreme multilabel classification (XMLC) model for extracting the top 25 terms as per matching score with thesaurus from an extensive biomedical database.
About Us
At Straive, we operationalize data analytics and AI for global enterprises. We leverage our unique people-process-tech framework to build the best-of-breed data analytics & AI solutions. By operationalizing this solution into your core workflow, we deliver real-world measurable impact and better ROIs through a combination of higher efficiency, elevated experiences, and enhanced revenues.
For more information about our services and how we can help you operationalize data analytics and AI, please visit our website: www.straive.com contact us at contact@straive.com.
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