Create dataset TALAA

Source: Masader Project

• uid: talaa
• entry: https://arbml.github.io/masader/card.html?54
• Link: https://github.com/saidziani/Arabic-News-Article-Classification
• License : unknown
• Year: 2015
• Language: ar
• Dialect: ar-MSA: (Arabic (Modern Standard Arabic))
• Domain: news articles
• Form: text
• Collection Style: crawling
• Description: collections of articles
• Volume: 57,827
• Unit: documents
• Ethical Risks: Low
• Provider: USTHB Algeria
• Derived From:
• Paper Title: Building TALAA, a Free General and Categorized Arabic Corpus
• Paper Link: https://www.scitepress.org/Papers/2015/53521/53521.pdf
• Script: Arab
• Tokenized: No
• Host: GitHub
• Access: Free
• Cost:
• Test Split: Yes
• Tasks: Topic Classification
• Evaluation Set?:
• Venue Title: ICAART
• Citations: 4
• Venue Type: conference
• Venue Name: Conference on Agents and Artificial Intelligence
• authors: Essma Selab,A. Guessoum
• affiliations: ,
• abstract: Arabic natural language processing (ANLP) has gained increasing interest over the last decade. However,
  the development of ANLP tools depends on the availability of large corpora. It turns out unfortunately that
  the scientific community has a deficit in large and varied Arabic corpora, especially ones that are freely
  accessible. With the Internet continuing its exponential growth, Arabic Internet content has also been
  following the trend, yielding large amounts of textual data available through different Arabic websites. This
  paper describes the TALAA corpus, a voluminous general Arabic corpus, built from daily Arabic
  newspaper websites. The corpus is a collection of more than 14 million words with 15,891,729 tokens
  contained in 57,827 different articles. A part of the TALAA corpus has been tagged to construct an
  annotated Arabic corpus of about 7000 tokens, the POS-tagger used containing a set of 58 detailed tags. The
  annotated corpus was manually checked by two human experts. The methodology used to construct TALAA
  is presented and various metrics are applied to it, showing the usefulness of the corpus. The corpus can be
  made available to the scientific community upon authorisation.
• Added by :
• Notes: The github and the paper states that they are 51K articles but the actual one is 83 articles