As more and more Arabic texts emerged on the Internet, extracting important information
from these Arabic texts is especially useful. As a fundamental technology, Named entity …

Sentiment analysis has become one of the most active research areas in natural language
processing, and the Arabic language retains its importance in this field. It is so because of …

An information retrieval (IR) system is the core of many applications, including digital library
management systems (DLMS). The IR-based DLMS depends on either the title with …

Dialogue generation is the automatic generation of a text response, given a user's input.
Dialogue generation for low-resource languages has been a challenging tasks for …

Aspect-based sentiment analysis (ABSA) aims to predict the sentiment polarity towards a
given aspect term in a sentence on the fine-grained level, which usually requires a good …

Previous work on Arabic information extraction has mainly focused on named entity
recognition and very little work has been done on Arabic relation extraction and event …

Abstract Named Entity Recognition (NER) is a natural language processing (NLP) task that
involves assigning labels like Person, Location, and Organization to words in text. While …

Abstract Arabic Named Entity Recognition (ANER) is a crucial task in natural language
processing that aims to identify and classify named entities in text into predefined categories …

The introduction of word embedding models has remarkably changed many Natural
Language Processing tasks. Word embeddings can automatically capture the semantics of …

Abstract Machine Reading Comprehension (MRC) is a task that enables machines to mirror
key cognitive processes involving reading, comprehending a text passage, and answering …