Given the success of the first and second workshops on Open-Source Arabic Corpora and Corpora Processing Tools (OSACT) in LREC 2014 and LREC 2016, the third workshop comes to encourage researchers and practitioners of Arabic language technologies, including computational linguistics (CL), natural language processing (NLP), and information retrieval (IR), to share and discuss their research efforts, corpora, and tools. The workshop will also give special attention on the wide variety of initiatives for the creation, use, and evaluation of Arabic as a type of Asian Language Resources and Technologies, which is one of LREC 2018 hot topics. In addition to the general topics of CL, NLP and IR, the workshop will give a special emphasis on a new Arabic Data challenge track.

Data Challenge Track
This year, we are introducing ArabicWeb16, a new Web dataset that is suitable for many research projects. ArabicWeb16 is a public Web crawl of 150M Arabic Web pages, crawled over the month of January 2016, with high coverage of dialectal Arabic (about 21%) as well as Modern Standard Arabic (MSA). One goal of the workshop is to define shared challenges using this dataset. We encourage submissions describing experiments for research tasks on the dataset. This includes (but not limited to) training word-embeddings, deduplication, cross-dialect search, question answering, dialect detection, knowledge-base population, entity search, blog search, text classification, and spam detection. Further details, including instructions on how to obtain the dataset, can be found here (https://sites.google.com/view/arabicweb16).

Topics of interest

*Corpora

Surveying and criticizing the design of available Arabic corpora, their associated and processing tools.
Availing new annotated corpora for NLP and IR applications such as named entity recognition, machine translation, sentiment analysis, text classification, and language learning.
Evaluating the use of crowdsourcing platforms for Arabic data annotation.

* Tools and Technologies

Language education e.g. L1 and L2.
Language modeling and word embeddings.
Tokenization, normalization, word segmentation, morphological analysis, part-of-speech tagging, etc.
Sentiment analysis, dialect identification, and text classification.
Dialect translation.

* ArabicWeb16 Data Challenge

Language modeling, Word embeddings.
Dialect detection, Cross-dialect search.
Entity search, Blog search, Deduplication, Spam detection.
Question answering, Knowledge-base population.
Text Classification.