Year: 2019
Type: conference-paper
Abstract: This paper describes the QC-GO team submission to the MADAR Shared Task Subtask 1 (travel domain dialect identification) and Subtask 2 (Twitter user location identification).In our participation in both subtasks, we explored a number of approaches and system combinations to obtain the best performance for both tasks.These include deep neural nets and heuristics.Since individual approaches suffer from various shortcomings, the combination of different approaches was able to fill some of these gaps.Our system achieves F1-Scores of 66.1% and 67.0% on the development sets for Subtasks 1 and 2 respectively.
DOI: 10.18653/v1/w19-4639
Authors: Younes Samih, Hamdy Mubarak, Ahmed Abdelali, Mohammed Attia, Mohamed Eldesouki, Kareem Darwish
Institution: Hamad bin Khalifa University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W2970575855