3 years ago

Graph-based Arabic NLP Techniques: A Survey

Wael Etaiwi, Arafat Awajan

Publication date: 2018

Source: Procedia Computer Science, Volume 142

Author(s): Wael Etaiwi, Arafat Awajan


The improvements of natural language processing applications such as machine translation, text summarization and the likes are crucial, and can be achieved using many different techniques including graph, deep learning, word embedding and others. This survey investigates several research studies that have been conducted in the field of Arabic natural language processing using graph representation. The related literature in the use of graph in Arabic Natural Language Processing is limited and relatively new compared to the available literature on other languages, such as English. This paper summarizes the major techniques used in Graph-based Arabic NLP techniques, and discusses the role of using graph based techniques to solve natural language processing problems.

You might also like
Discover & Discuss Important Research

Keeping up-to-date with research can feel impossible, with papers being published faster than you'll ever be able to read them. That's where Researcher comes in: we're simplifying discovery and making important discussions happen. With over 19,000 sources, including peer-reviewed journals, preprints, blogs, universities, podcasts and Live events across 10 research areas, you'll never miss what's important to you. It's like social media, but better. Oh, and we should mention - it's free.

  • Download from Google Play
  • Download from App Store
  • Download from AppInChina

Researcher displays publicly available abstracts and doesn’t host any full article content. If the content is open access, we will direct clicks from the abstracts to the publisher website and display the PDF copy on our platform. Clicks to view the full text will be directed to the publisher website, where only users with subscriptions or access through their institution are able to view the full article.