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Structured Prediction for Joint Class Cardinality and Entity Property Inference in Model-Complete Text Comprehension
We show that cardinality prediction can successfully be approached by modeling the overall task as a joint inference problem, predicting the number of individuals of certain classes while at the same time extracting their properties.
SANTO: A Web-based Annotation Tool for Ontology-driven Slot Filling
Supervised machine learning algorithms require training data whose generation for complex relation extraction tasks tends to be difficult.
Predicting Disease-Gene Associations using Cross-Document Graph-based Features
In the context of personalized medicine, text mining methods pose an interesting option for identifying disease-gene associations, as they can be used to generate novel links between diseases and genes which may complement knowledge from structured databases.
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