ClassifiR simplifies the task of labeling and categorizing entire documents based on predefined taxonomies, industry classifications, or customized label sets. It works seamlessly with StructR, which identifies text segment properties, providing a comprehensive data analysis solution. With a user-friendly graphical interface, ClassifiR facilitates the creation and exploration of custom ontologies through clustering, labeling, and querying.
Data extraction and structuring from unstructured text sources have always been a challenging task in the field of data analytics. To tackle this challenge, we introduce StructR, a powerful component within the enRichMyData toolbox that specializes in extracting structured data from textual content. StructR offers a range of advanced techniques, including entity recognition and linking,
In the good old days of machine learning and data mining, in the era of nearest neighbours, decision trees, linear regression and naive Bayes, the limitations of these models were clear. They worked surprisingly well in many cases, especially if the underlying data was rich enough. But are they comparable to the human brain? Read
DiscoverR tools help users find and understand data that they can use in their data enrichment processes
DiscoverR tools are the components of the enRichMyData toolbox that help users find and understand data that they can use in their data enrichment processes. Since knowledge graphs (KGs) play a crucial role in data enrichment, either as target data sources of interest or as bridges to reach additional sources, the first DiscoverR tool, ABSTAT,
In his recent work, Krisztian Buza challenged the aforementioned “widely acknowledged truth” in context of data augmentation. His observations show that rich training data may be much more valuable than augmented (i.e., artificially generated) data, and – most importantly – the advantage of a sophisticated algorithm relative to a simple algorithm may not be easily