Search Results for author:
Found 7 papers, 4 papers with code
A Novel Framework for Detecting Important Subevents from Crisis Events via Dynamic Semantic Graphs
Furthermore, we show that our approach significantly outperforms event detection baselines, highlighting the importance of aggregating information across tweets for our task.
XLTime: A Cross-Lingual Knowledge Transfer Framework for Temporal Expression Extraction
To date, work in this area has mostly focused on English as there is a scarcity of labeled data for other languages.
GTN-ED: Event Detection Using Graph Transformer Networks
Recent works show that the graph structure of sentences, generated from dependency parsers, has potential for improving event detection.
Clustering of Social Media Messages for Humanitarian Aid Response during Crisis
Social media has quickly grown into an essential tool for people to communicate and express their needs during crisis events.
Models for Capturing Temporal Smoothness in Evolving Networks for Learning Latent Representation of Nodes
However, existing models for learning latent representation are inadequate for obtaining the representation vectors of the vertices for different time-stamps of a dynamic network in a meaningful way.
Dis-S2V: Discourse Informed Sen2Vec
Our first approach retrofits (already trained) Sen2Vec vectors with respect to the network in two different ways: (1) using the adjacency relations of a node, and (2) using a stochastic sampling method which is more flexible in sampling neighbors of a node.
A large scale study of SVM based methods for abstract screening in systematic reviews
However, it is very hard to clearly understand the applicability of these methods in a systematic review platform because of the following challenges: (1) the use of non-overlapping metrics for the evaluation of the proposed methods, (2) usage of features that are very hard to collect, (3) using a small set of reviews for the evaluation, and (4) no solid statistical testing or equivalence grouping of the methods.
