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Procedia Computer Science
Article . 2018 . Peer-reviewed
License: CC BY NC ND
Data sources: Crossref
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Procedia Computer Science
Article
License: CC BY NC ND
Data sources: UnpayWall
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Graph-based Arabic NLP Techniques: A Survey

Authors: Wael Etaiwi; Arafat Awajan;

Graph-based Arabic NLP Techniques: A Survey

Abstract

Abstract 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.

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    7
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Top 10%
Average
Top 10%
gold