With the widespread growth of data on the Web, the need for efficient methods to get and
arrange valuable information from these big noisy data is increased. The knowledge graph …

Text classification pertains to the automated procedure of assigning predefined labels or
categories to textual data. A comprehensive review of the existing literature on Arabic text …

Nowadays, group decision making is an everyday occurrence in different scenarios, such as
marketing or social networks. These social networks have facilitated communication …

Abstract In Natural Language Processing (NLP) domain, the majority of automatic text
summarization approaches depend on a prior knowledge of the language and/or the …

One of the most important phases in text processing is stemming, whose aim is to aggregate
all variations in a word into one group to aid natural language processing. The …

Abstract Concepts extraction is the backbone task for an ontology construction system.
Identifying the relevant concepts is considered one of the main challenges of automatic …

This study addresses the critical issue of user comprehension and application within the
sphere of cloudbased Enterprise Resource Planning (ERP) systems, a recurrent challenge …

The widespread use of social media has created a wealth of Arabic textual data, presenting
challenges for NLP researchers due to the complexity and characteristics of the Arabic …

Stemming is an essential step in various Natural Language Processing (NLP) applications
and is used to reduce different variants of the query words to a standard form to avoid the …

This research presents a new algorithm for Arabic root extraction, which aims to improve the
accuracy of Arabic Natural Language Processing Algorithms by addressing the weaknesses …