161 citations · 289 across the 26 of their papers we have counts for
6 papers · 1 filter
On the Effectiveness of the Pooling Methods for Biomedical Relation Extraction with Deep Learning
Tuan Ngo Nguyen, Franck Dernoncourt, Thien Huu Nguyen
Deep learning models have achieved state-of-the-art performances on many relation extraction datasets. A common element in these deep learning models involves the pooling mechanism…
Improving Slot Filling by Utilizing Contextual Information
Amir Pouran Ben Veyseh, Franck Dernoncourt, Thien Huu Nguyen
Slot Filling (SF) is one of the sub-tasks of Spoken Language Understanding (SLU) which aims to extract semantic constituents from a given natural language utterance. It is formulat…
A Joint Model for Definition Extraction with Syntactic Connection and Semantic Consistency
Amir Pouran Ben Veyseh, Franck Dernoncourt, Dejing Dou +1
Definition Extraction (DE) is one of the well-known topics in Information Extraction that aims to identify terms and their corresponding definitions in unstructured texts. This tas…
Extending Event Detection to New Types with Learning from Keywords
Viet Dac Lai, Thien Huu Nguyen
Traditional event detection classifies a word or a phrase in a given sentence for a set of predefined event types. The limitation of such predefined set is that it prevents the ada…
Improving Cross-Domain Performance for Relation Extraction via Dependency Prediction and Information Flow Control
Amir Pouran Ben Veyseh, Thien Huu Nguyen, Dejing Dou
Relation Extraction (RE) is one of the fundamental tasks in Information Extraction and Natural Language Processing. Dependency trees have been shown to be a very useful source of i…
Graph based Neural Networks for Event Factuality Prediction using Syntactic and Semantic Structures
Amir Pouran Ben Veyseh, Thien Huu Nguyen, Dejing Dou
Event factuality prediction (EFP) is the task of assessing the degree to which an event mentioned in a sentence has happened. For this task, both syntactic and semantic information…