Arabic community question answering. (19th December 2018)
- Record Type:
- Journal Article
- Title:
- Arabic community question answering. (19th December 2018)
- Main Title:
- Arabic community question answering
- Authors:
- NAKOV, PRESLAV
MÀRQUEZ, LLUÍS
MOSCHITTI, ALESSANDRO
MUBARAK, HAMDY - Abstract:
- Abstract: We analyze resources and models for Arabic community Question Answering (cQA). In particular, we focus on CQA-MD, our cQA corpus for Arabic in the domain of medical forums. We describe the corpus and the main challenges it poses due to its mix of informal and formal language, and of different Arabic dialects, as well as due to its medical nature. We further present a shared task on cQA at SemEval, the International Workshop on Semantic Evaluation, based on this corpus. We discuss the features and the machine learning approaches used by the teams who participated in the task, with focus on the models that exploit syntactic information using convolutional tree kernels and neural word embeddings. We further analyze and extend the outcome of the SemEval challenge by training a meta-classifier combining the output of several systems. This allows us to compare different features and different learning algorithms in an indirect way. Finally, we analyze the most frequent errors common to all approaches, categorizing them into prototypical cases, and zooming into the way syntactic information in tree kernel approaches can help solve some of the most difficult cases. We believe that our analysis and the lessons learned from the process of corpus creation as well as from the shared task analysis will be helpful for future research on Arabic cQA.
- Is Part Of:
- Natural language engineering. Volume 25:Part 1(2019)
- Journal:
- Natural language engineering
- Issue:
- Volume 25:Part 1(2019)
- Issue Display:
- Volume 25, Issue 1, Part 1 (2019)
- Year:
- 2019
- Volume:
- 25
- Issue:
- 1
- Part:
- 1
- Issue Sort Value:
- 2019-0025-0001-0001
- Page Start:
- 5
- Page End:
- 41
- Publication Date:
- 2018-12-19
- Subjects:
- Natural language processing (Computer science) -- Periodicals
Software engineering -- Periodicals
006.35 - Journal URLs:
- http://journals.cambridge.org/action/displayJournal?jid=NLE ↗
- DOI:
- 10.1017/S1351324918000426 ↗
- Languages:
- English
- ISSNs:
- 1351-3249
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 9521.xml