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Found 5 papers, 2 papers with code
ChemNER: Fine-Grained Chemistry Named Entity Recognition with Ontology-Guided Distant Supervision
For example, chemistry research needs to study dozens to hundreds of distinct, fine-grained entity types, making consistent and accurate annotation difficult even for crowds of domain experts.
Early prediction of onset of sepsis in Clinical Setting
The model achieved a normalized utility score of 0. 494 on test data and 0. 378 on prospective data at threshold 0. 3.
MotifClass: Weakly Supervised Text Classification with Higher-order Metadata Information
We study the problem of weakly supervised text classification, which aims to classify text documents into a set of pre-defined categories with category surface names only and without any annotated training document provided.
Improving Answer Selection and Answer Triggering using Hard Negatives
In this paper, we establish the effectiveness of using hard negatives, coupled with a siamese network and a suitable loss function, for the tasks of answer selection and answer triggering.
CVBed: Structuring CVs usingWord Embeddings
Automatic analysis of curriculum vitae (CVs) of applicants is of tremendous importance in recruitment scenarios.
