Papers by Batuhan Bardak

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Papers by Batuhan Bardak

NAACL

N19-1

noisy short text
convolutional neural network
CNN
long short-term memory
LSTM
recurrent neural network
word level meta-embeddings
traditional and neural baselines
cyber-crime prevention
detecting cyber security events

2019

Representation Learning

1 papers

Detecting Cybersecurity Events from Noisy Short Text (N19-1)

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Semih Yagcioglu, Mehmet Saygin Seyfioglu, Begum Citamak, Batuhan Bardak, Seren Guldamlasioglu, Azmi Yuksel, Emin Islam Tatli

Representation Learning

Challenge:	Using domain-specific word embeddings, we propose a method to detect cyber security events from noisy short text.
Approach:	They propose a method that leverages domain-specific word embeddings and task-specific features to detect cyber security events from tweets.
Outcome:	The proposed model outperforms both baselines and traditional models on a dataset of 2K tweets and manually annotates them.

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