PhD, 2009
University of Georgia - Athens, Georgia, USA
http://www.uga.edu

Thesis: "Ontology-Driven Question Answering and Ontology Quality Evaluation"
Advisor: Dr. I. Budak Arpinar

MSc, 2003
University of Jordan - Amman, Jordan
http://www.ju.edu.jo

Thesis: "Data Migration from Relational Databases into Multidimensional Databases"
Advisors: Dr. Riad Jabri and Dr. Munib Qutaishat

BSc, 1998
University of Jordan - Amman, Jordan

http://www.ju.edu.jo


PhD Thesis

Title: "Ontology-Driven Question Answering and Ontology Quality Evaluation"
Advisory Committee: Dr. I. Budak Arpinar (Major Professor), Dr. John A. Miller and Dr. Liming Cai.

Abstract:

As more data is being semantically annotated, it is getting more common that researchers in multiple disciplines to rely on semantic repositories that contain large amounts of data in the form of ontologies as a compact source of information. One of the main issues currently facing these researchers is the lack of easy-to-use interfaces for data retrieval, due to the need to use special query languages or applications. In addition, the knowledge in these repositories might not be comprehensive or up-to-date due to several reasons, such as the discovery of new knowledge in the field after the repositories was created. In this dissertation, we present our SemanticQA system that allows users to query semantic data repositories using natural language questions. If a user question cannot be answered solely from the ontology, SemanticQA detects the failing parts and attempts to answer these parts from web documents and plugs in the answers to answer the whole questions, which might involve a repetition of the same process if other parts fail.

At the same time, with the large number of ontologies being added constantly, it is difficult for users to find ontologies that are suitable to their work. Therefore, tools for evaluating and ranking the ontologies are needed. For this purpose, we present OntoQA, a tool that evaluates ontologies related to a certain set of terms and then ranks them according a set of metrics that captures different aspects of ontologies. Since there are no global criteria defining how a good ontology should be, OntoQA allows users to tune the ranking towards certain features of ontologies to suit the need of their applications. OntoQA is not only useful for users trying to find suitable ontologies, but for ontology developers who are looking for measures to evaluate their product.

Courses Taken

Human Computer Interaction, Advanced Databases, Special Topics, Database Management, Parallel Processing and Computational Science, Enterprise Integration, Software Engineering, Advanced Information Systems, Statistical Methods I, Statistical Methods II, Algorithms, Operating Systems, Computer Systems Architecture.


MSc Thesis

Title: "Data Migration from Relational Databases into Multidimensional Databases"
Advisory Committee: Dr. Riad Jabri (Major Professor), Dr. Munib Qutaishat (co-Advisor), Dr. Rehab Al-Duwairi, Dr. Sami Sarhan and Dr. Khalil Al-Hindi.

Abstract:

The research work reported here introduces a new model, called Relational to Multidimensional Model (RMM), for migrating data from relational databases into multidimensional databases. Based on this model, it includes a new application called Relational to Multidimensional Shell (RMS). RMM and RMS were designed to migrate data stored in a relational database, into a multidimensional database.

RMM defines a shell on top of the relational database that gives the multidimensional look to it. This shell contains all the information the user during the data analysis. At the same time, it allows the normal (relational) usage of the database to perform as if the shell does not exist. RMS is a useful tool for data analysis, as it allows the user to select subranges of data within a dimension when the number of elements in that dimension is large. RMS also gives the user the opportunity to choose the measure he wants to analyze, and the dimensions he wants to use in his analysis.

RMM defines useful multidimensional operations, and RMS implements them. These operations allow presented in a user-friendly graphical interface dynamically analyze data stored in a relational database and executes users' queries on large data volumes in a timely manner. They also provide a facility to export the resulting cube data into a Microsoft Excel sheet for any further analysis and formatting that might be needed. All these features were achieved without having to learn any new languages, and without having to install or buy new expensive software or hardware.

Courses Taken

Theory of Algorithms, Selected Topics, Operating Systems, Artificial Intillegence and Expert Systems, Databases, Numerical Simulation Methods, Software Engineering, Programming Language Design.