Waseem Alromima

Waseem Alromima
Taibah University · Information System

Associate Professor in Information Systems

About

24
Publications
11,303
Reads
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176
Citations
Introduction
Ph.D. Information Systems Faculty of Computer and Information Science, at Ain Shams University, M.Sc Degree in Information Systems from University of Jordan - Amman I am interested in researchers of IR, NLP, Machine Learning, Arabic text Processing.... My Ph.D. thesis was titled "Semantic-based system for Arabic Information Retrieval". contact: waseem.2020 at yahoo dot com
Additional affiliations
February 2012 - November 2016
Ain Shams University
Position
  • PhD
February 2010 - July 2010
University of Jordan
Position
  • Phrase Extraction From A Tagged Arabic Quranic Corpus
Description
  • This research presents a phrase extraction system for Arabic documents using a tagged Arabic corpus, noun phrase (NP), verb phrase (VP), preposition phrase (PP), particle constructions (Special), and N-Gram phrases.

Publications

Publications (24)
Article
The novel human Corona disease (COVID-19) is a pulmonary sickness brought on by an extraordinarily outrageous respiratory condition crown 2. (SARS-CoV-2). Chest radiography imaging has a significant role in the screening, early diagnosis, and follow-up of the suspected individuals due to the effects of COVID-19 on pneumonic-sensitive tissue. It als...
Article
Full-text available
Coronavirus pandemic has created complex challenges and adverse conditions. Sentiment analysis is a process of studying the user application. Because of using the internet in daily activities, many domains and organizations concentrate on analysis or getting user feedback to take the right decision. This paper is review the existing applications th...
Chapter
This study proposed a weighted fractional grey model (WFGM) based on a genetic algorithm for forecasting annual electricity consumption. WFGM has two parameters that can be used to adjust the order of the summation based on different data sequences and reflect the new information priority. The key issue with the WFGM model is determining two optimu...
Chapter
Full-text available
Textual data streams have been widely applied in real-world applications where online users’ expressed their opinions for online products. Mining this stream of data is a challenging task for researchers as a result of changes in data distribution, a phenomenon widely known as concept drift. Most of the existing classification methods incorporated...
Article
Full-text available
Sentiment analysis plays an important role in obtaining speakers' opinions or feelings towards events, products, topics, or services, helping businesses to improve their products. Moreover, governments and organizations investigate and solve current social issues by analyzing perspectives and feelings. This study evaluated the habit of chewing Khat...
Chapter
Social media platforms have a main role in hate crimes worldwide. Detecting hate speech from social media is a big challenge. Many studies utilized machine learning methods for classifying the text as hate speech. However, the performance of machine learning method differs when using different parameters settings. Selecting the best values of param...
Chapter
The word expansion task has applicability in information retrieval and question answering systems. It relieves the vocabulary mismatch problem leading to a higher recall. The recent word embedding models demonstrated merit for the word expansion task in comparison to the traditional n-gram models. However, to acquire quality embeddings in each lang...
Article
Due to the rapid and increased availability of documents in a digital format, effect for retrieving information with highest accuracy and the lowest error rate is becoming more difficult. Text Classification (TC) has become one of the key techniques for controlling and organizing documents based on the content of documents. Therefore, keyword extra...
Article
In the era of information overloading, information retrieval systems are vital applications. Many researchers try to enhance the search results by introducing new methods. Unlike the English language, some languages like Arabic have complex morphological aspects and lack both linguistic and semantic resources. This paper proposes a language-indepen...
Article
Full-text available
The semantic resources are important parts in the Information Retrieval (IR) such as search engines, Question Answering (QA), etc., these resources should be available, readable and understandable. In semantic web, the ontology plays a central role for the information retrieval, which use to retrieves more relevant information from unstructured inf...
Conference Paper
Ontology is an explicit specification of conceptualization. It defines the terms with specified relationships between them and can be interpreted by both humans and computers. In general, there are scare semantic resources for Arabic language especially in Arabic ontologies. These semantic resources are very essential components in both Information...
Conference Paper
The Arabic language is the spoken language in the Semitic languages groups, which is spoken by more than 422 million people. It is the language of the Islamic Holy Quran, so all the Muslims should learn it. In general, there is a shortage in semantic resources for the Arabic language especially in Arabic ontologies. These semantic resources are imp...
Conference Paper
Information Extraction (IE) is one of the most important Natural Language Processing (NLP) applications, which extracts information such as Named-Entities (NE) and collocation of terms from the corpus. Collocation is a sequence of terms that co-occur together in the corpus. In Arabic Information Extraction, there are many problems because of the co...
Article
Information Extraction (IE) is one of the most important Natural Language Processing (NLP) applications, which extracts information such as Named-Entities (NE) and collocation of terms from the corpus. Collocation is a sequence of terms that co-occur together in the corpus. In Arabic Information Extraction, there are many problems because of the co...
Article
Text Classification (TC) or text categorization can be described as the act of assigning text documents to predefined classes or categories. The need for automatic text classification came from the large amount of electronic documents on the web. The classification accuracy is affected by the documents content and the classification technique being...
Chapter
Full-text available
In this paper, an experimental study was conducted on three techniques for Arabic text classification. These techniques are Support Vector Machine (SVM) with Sequential Minimal Optimization (SMO), Naïve Bayesian (NB), and J48. The paper assesses the accuracy for each classifier and determines which classifier is more accurate for Arabic text classi...
Conference Paper
This paper compares three techniques for Arabic text classification; these techniques are Support Vector Machine (SVM) with Sequential Minimal Optimization (SMO), Naïve Bayesian (NB), and J48. The main objective of this paper is to measure the accuracy for each classifier and to determine which classifier is more accurate for Arabic text classifica...
Article
Full-text available
ABSTRACT This paper compares three techniques for Arabic text classification; these techniques are Support Vector Machine (SVM) with Sequential Minimal Optimization (SMO), Naïve Bayesian (NB), and J48. The main objective of this paper is to measure the accuracy for each classifier and to determine which classifier is more accurate for Arabic text c...

Questions

Questions (8)
Question
Precision, Recall and MAP are calculated in our Information Retrieval System (IRS).
Question
Synonymy means that one of two or more words in the same language have the same meaning, and polysemy means that many individual words have more than one meaning.
Question
In the English language there are a lot of tools to represent the knowledge from document in the conceptual graph, like CharGare, etc. at http://conceptualgraphs.org/.
Question
Conceptual Graph from the knowledge representation and in the semantic notion. In the English language there are a lot of tools to represent the knowledge from document in the conceptual graph, like CharGare, Ameen at http://conceptualgraphs.org/.
Question
what is the differences.
I want to know the different concepts for all.
Question
I have chosen to study books in KR and I find many books in the same subject, but related to reasoning and artificial intelligence.
My area of expertise is information retrieval and natural language processing and I was hoping someone could help me in my search. Any suggestions?
Question
Knowledge Representation (KR) it's a good method to extract relevant information or document to the users' needs. We need this technique in the e-learning application.
Question
The tagged Corpus we have for Arabic Language is for the Holy Quran.

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