Machine Learning Use Cases
KBpedia, combined with your own schema and data, can provide a nearly
automated foundation for creating trainng corpuses and training sets for
deep learning, unsupervised learning, and supervised learning. Further,
these same selection capabilities, combined with the logical basis of the
KBpedia knowledge graph, also aid the creation of reference standards.
Reference standards are essential for tuning analysis parameters to
obtain the best results for your tagging or categorization efforts.
Tuning parameters are integral to most forms of natural language
processing and for supervised learning.
There is a bit more
explanation of machine
learning
on this site. Also, here are some of the use cases
we have conducted relevant to machine learning: