Information Technology Collage / Department of Computer Science

عاهد مليح فلاح السبوع


Teacher
عاهد مليح فلاح السبوع

Curriculum Vitae
  • Major:
  • College: Information Technology Collage
  • Department(s): Computer Science Department
  • E-mail: ahed_alsbou@ahu.edu.jo
  • Phone No.: 00962775639040

Ahed Al-Sbou is a lecturer in the Information Technology School of Computer Science at the University of Al-Hussein Bin Talal where he has been a faculty member since 2014. He holds the master degree in computer science.
Ahed completed his Master degree from Al-Balqa Applied University, Salt, Jordan in 2012 and his B.S. degree in computer science from Al-Hussein Bin Talal University, Ma'an, Jordan in 2006. His research interests lie in computer science are in the area of programming languages, ranging from theory to design to implementation, Data base, Data Mining, Natural languages Processing (NLP), and information systems.  
Ahed has worked as a computer lab supervisor (2006-2014) at Al-Hussein Bin Talal University.

Last updated: November 2018

My research interests lie in computer science:

1. in the area of programming languages

2. Data base

3. Data Mining


A Survey of Arabic Text Classification Models
  • Research Summary
  • There is a huge content of Arabic text available over online that requires an organization of these texts. As result, here are many applications of natural languages processing (NLP) that concerns with text organization. One of the is text classification (TC). TC helps to make dealing with unorganized text. However, it is easier to classify them into suitable class or labels. This paper is a survey of Arabic text classification. Also, it presents comparison among different methods in the classification of Arabic texts, where Arabic text is represented a complex text due to its vocabularies. Arabic language is one of the richest languages in the world, where it has many linguistic bases. The researche in Arabic language processing is very few compared to English. As a result, these problems represent challenges in the classification, and organization of specific Arabic text. Text classification (TC) helps to access the most documents, or information that has already classified into specific classes, or categories to one or more classes or categories. In addition, classification of documents facilitate search engine to decrease the amount of document to, and then to become easier to search and matching with queries.
  • Research link
  • key words
    Arabic language processing Arabic text categorization Arabic text mining Classification algorithms Clustering algorithms Natural languages processing Text classification
Semantic Clustering of Functional Requirements Using Agglomerative Hierarchical Clustering
  • Research Summary
  • Software applications have become a fundamental part in the daily work of modern society as they meet different needs of users in different domains. Such needs are known as software requirements (SRs) which are separated into functional (software services) and non-functional (quality attributes). The first step of every software development project is SR elicitation. This step is a challenge task for developers as they need to understand and analyze SRs manually. For example, the collected functional SRs need to be categorized into different clusters to break-down the project into a set of sub-projects with related SRs and devote each sub-project to a separate development team. However, functional SRs clustering has never been considered in the literature. Therefore, in this paper, we propose an approach to automatically cluster functional requirements based on semantic measure. An empirical evaluation is conducted using four open-access software projects to evaluate our proposal. The experimental results demonstrate that the proposed approach identifies semantic clusters according to well-known used measures in the subject.
  • Research link
  • key words
    requirements elicitation; functional requirements; semantic clustering; hierarchical clustering; software requirement specifications
A Survey of Arabic Text Classification Models
  • Research Summary
  • There is a huge content of Arabic text available over online that requires an organization of these texts. As result, here are many applications of natural languages processing (NLP) that concerns with text organization. One of the is text classification (TC). TC helps to make dealing with unorganized text. However, it is easier to classify them into suitable class or labels. This paper is a survey of Arabic text classification. Also, it presents comparison among different methods in the classification of Arabic texts, where Arabic text is represented a complex text due to its vocabularies. Arabic language is one of the richest languages in the world, where it has many linguistic bases. The researche in Arabic language processing is very few compared to English. As a result, these problems represent challenges in the classification, and organization of specific Arabic text. Text classification (TC) helps to access the most documents, or information that has already classified into specific classes, or categories to one or more classes or categories. In addition, classification of documents facilitate search engine to decrease the amount of document to, and then to become easier to search and matching with queries.
  • Research link
  • key words
    Arabic language processing Arabic text categorization Arabic text mining Classification algorithms Clustering algorithms Natural languages processing Text classification
Semantic Clustering of Functional Requirements Using Agglomerative Hierarchical Clustering
  • Research Summary
  • Software applications have become a fundamental part in the daily work of modern society as they meet different needs of users in different domains. Such needs are known as software requirements (SRs) which are separated into functional (software services) and non-functional (quality attributes). The first step of every software development project is SR elicitation. This step is a challenge task for developers as they need to understand and analyze SRs manually. For example, the collected functional SRs need to be categorized into different clusters to break-down the project into a set of sub-projects with related SRs and devote each sub-project to a separate development team. However, functional SRs clustering has never been considered in the literature. Therefore, in this paper, we propose an approach to automatically cluster functional requirements based on semantic measure. An empirical evaluation is conducted using four open-access software projects to evaluate our proposal. The experimental results demonstrate that the proposed approach identifies semantic clusters according to well-known used measures in the subject.
  • Research link
  • key words
    requirements elicitation; functional requirements; semantic clustering; hierarchical clustering; software requirement specifications

v  Lecturer – Faculty of Information Technology- University of Al-hussien Bin

Talal, Maan-Jordan (2. February 2014 up to date).

v  Supervisor of Computer Lab - University of Al-Hussein Bin Talal - Ma'an - Jordan – (18.June.2006 - 2. February 2014  ).

v  Work as a teacher at Grain Secondary School for four months (2006).

v  Part-time Lecturer - Faculty of Information Technology - University of Al-Hussein Bin Talal - a period of three semesters, Jordan.

v  Teaching  of the programming language C + + subject (3 credit hours) in the second semester of the academic year (2012 /2013). Al-Hussein Bin Talal University

v  Teaching of the Fundamentals to information technology subject (6 credit hours) in the first semester of the academic year (2013 /2014). Al-Hussein Bin Talal University

v  I have a the local Jordanian national test in English.

Computer science

1- Object Oriented Programming Language
2- Fundamentals to information technology
3- C ++ programming language
4- Visual Basic language
5-Computer skills

 

Academic qualifications and certificates

1-MS in Computer Science
Al-Balqa Applied University, Jordan
September 2009 — August 2012
2-BS in Computer Science
Al Hussein bin Talal University, Jordan
September 2002 — February 2006
3-High School Certificate, Science Stream
Ministry of Education, Jordan
September 2001 — August 2002

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