Fetching the paper…
Reading the bibliography…
This paper tackles the problem of open domain factual Arabic question answering (QA) using Wikipedia as our knowledge source.
Nltk: The natural language toolkit
Steven Bird. 2006 · 2006
Earlier work this paper cites.
Implementation of the arabiqa question answering system’s components
Abdelouahid Lyhyaoui Benajiba Yassine, Paolo Rosso. 2007 · 2007
Earlier work this paper cites.
An evaluated semantic query expansion and structure-based approach for enhancing arabic question/answering
Karim Bouzouba Abouenour Lahsen and Paolo Rosso. 2010 · 2010
Earlier work this paper cites.
Defarabicqa: Arabic definition question answering system
Omar Trigui, Lamia Hadrich Belguith, and Paolo Rosso. 2010 · 2010
Earlier work this paper cites.
Qarabpro: A rule based question answering system for reading comprehension tests in arabic
Mohammed Akour, Sameer Abufardeh, Kenneth Magel, and Qasemm Al-Radaideh. 2011 · 2011
Earlier work this paper cites.
Overview of qa4mre at clef 2011: Question answering for machine reading evaluation
Eduard H. Hovy Pamela Forner Álvaro Rodrigo Richard FE Sutcliffe Corina Forascu Peñas, Anselmo and Caroline Sporleder. 2011 · 2011
Earlier work this paper cites.
Mctest: A challenge dataset for the open-domain machine comprehension of text
Matthew Richardson, Christopher JC Burges, and Erin Renshaw. 2013 · 2013
Earlier work this paper cites.
Madamira: A fast, comprehensive tool for morphological analysis and disambiguation of arabic
Arfath Pasha, Mohamed Al-Badrashiny, Mona Diab, Ahmed El Kholy, Ramy Eskander, Nizar Habash, Manoj Pooleery, Owen Rambow, and Ryan Roth. 2014 · 2014
Earlier work this paper cites.
Arabic question answering: systems, resources, tools, and future trends
Mohamed Shaheen and Ahmed Magdy Ezzeldin. 2014 · 2014
Earlier work this paper cites.
Deep learning models for sentiment analysis in arabic
Ahmad Al Sallab, Hazem Hajj, Gilbert Badaro, Ramy Baly, Wassim El Hajj, and Khaled Bashir Shaban. 2015 · 2015
Earlier work this paper cites.
Answer selection in arabic community question answering: A feature-rich approach
Yonatan Belinkov, Alberto Barrón-Cedeño, and Hamdy Mubarak. 2015 · 2015
Cited alongside, same era.
Dbpedia–a large-scale, multilingual knowledge base extracted from wikipedia
Jens Lehmann, Robert Isele, Max Jakob, Anja Jentzsch, Dimitris Kontokostas, Pablo N Mendes, Sebastian Hellmann, Mohamed Morsey, Patrick Van Kleef, Sören Auer, et al. 2015 · 2015
Cited alongside, same era.
Answering arabic why-questions: Baseline vs. rst-based approach
Aqil M Azmi and Nouf A Alshenaifi. 2016 · 2016
Cited alongside, same era.
Fasttext.zip: Compressing text classification models
Armand Joulin, Edouard Grave, Piotr Bojanowski, Matthijs Douze, Hérve Jégou, and Tomas Mikolov. 2016 · 2016
Cited alongside, same era.
Squad: 100,000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016
Newsqa: A machine comprehension dataset
Adam Trischler, Tong Wang, Xingdi Yuan, Justin Harris, Alessandro Sordoni, Philip Bachman, and Kaheer Suleman. 2017 · 2017
Later among the works it cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, ukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Later among the works it cites.
Ema at semeval-2018 task 1: Emotion mining for arabic
Gilbert Badaro, Obeida El Jundi, Alaa Khaddaj, Alaa Maarouf, Raslan Kain, Hazem Hajj, and Wassim El-Hajj. 2018 · 2018
Later among the works it cites.
Multi-step retriever-reader interaction for scalable open-domain question answering
Rajarshi Das, Shehzaad Dhuliawala, Manzil Zaheer, and Andrew McCallum. 2018 · 2018
Later among the works it cites.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Bidirectional attention flow for machine comprehension
Minjoon Seo, Aniruddha Kembhavi, Ali Farhadi, and Hannaneh Hajishirzi. 2016 · 2016
Cited alongside, same era.
Google’s neural machine translation system: Bridging the gap between human and machine translation
Yonghui Wu, Mike Schuster, Zhifeng Chen, Quoc V Le, Mohammad Norouzi, Wolfgang Macherey, Maxim Krikun, Yuan Cao, Qin Gao, Klaus Macherey, et al. 2016 · 2016
Cited alongside, same era.
Reading wikipedia to answer open-domain questions
Danqi Chen, Adam Fisch, Jason Weston, and Antoine Bordes. 2017 · 2017
Cited alongside, same era.
Triviaqa: A large scale distantly supervised challenge dataset for reading comprehension
Mandar Joshi, Eunsol Choi, Daniel S Weld, and Luke Zettlemoyer. 2017 · 2017
Cited alongside, same era.
Semeval-2017 task 3: Community question answering
Preslav Nakov, Doris Hoogeveen, Lluís Màrquez, Alessandro Moschitti, Hamdy Mubarak, Timothy Baldwin, and Karin Verspoor. 2017 · 2017
Cited alongside, same era.
R 3: Reinforced ranker-reader for open-domain question answering
Shuohang Wang, Mo Yu, Xiaoxiao Guo, Zhiguo Wang, Tim Klinger, Wei Zhang, Shiyu Chang, Gerry Tesauro, Bowen Zhou, and Jing Jiang. 2018a
Cited in the paper.
Joint training of candidate extraction and answer selection for reading comprehension
Zhen Wang, Jiachen Liu, Xinyan Xiao, Yajuan Lyu, and Tian Wu. 2018b
Cited in the paper.
Dawqas: A dataset for arabic why question answering system
Walaa Saber Ismail and Masun Nabhan Homsi. 2018 · 2018
Later among the works it cites.
Denoising distantly supervised open-domain question answering
Yankai Lin, Haozhe Ji, Zhiyuan Liu, and Maosong Sun. 2018 · 2018
Later among the works it cites.
Wikiqa: A challenge dataset for open-domain question answering
Yi Yang, Wen-tau Yih, and Christopher Meek. 2015 · 2018
Later among the works it cites.
Qanet: Combining local convolution with global self-attention for reading comprehension
Adams Wei Yu, David Dohan, Minh-Thang Luong, Rui Zhao, Kai Chen, Mohammad Norouzi, and Quoc V Le. 2018 · 2018
Later among the works it cites.
Natural questions: a benchmark for question answering research
Tom Kwiatkowski, Jennimaria Palomaki, Olivia Redfield, Michael Collins, Ankur Parikh, Chris Alberti, Danielle Epstein, Illia Polosukhin, Matthew Kelcey, Jacob Devlin, Kenton Lee, Kristina N. Toutanova, Llion Jones, Ming-Wei Chang, Andrew Dai, Jakob Uszkoreit, Quoc Le, and Slav Petrov. 2019 · 2019
Closest in time.