Extracting instances to improve semantic matching in the domain of renewable energy
Other Title(s)
استخراج الحالات لتحسين المطابقة الدلالي في مجال الطاقة المجددة
Dissertant
Thesis advisor
Comitee Members
Abu Jassar, Radwan
Ahmad, Ali Asad
University
Middle East University
Faculty
Faculty of Information Technology
Department
Department of Computer Information Systems
University Country
Jordan
Degree
Master
Degree Date
2014
English Abstract
Renewable energy (RE) has many resources, and the increased usage of these resources led to the spread of renewable energy applications.
These applications and services are provided by different providers.
Those providers use different architectures for their RE systems which are considered not compatible.
On the other hand, the providers have many ways to describe their services which considered as a big challenge that may face the customers.
This research explores the possibility to automate an environment whereby the customers can find the appropriate services provider that meets their requirements.
Moreover, this research presents ontology in the domain of RE.
This research explores the possibility to measure the distance between the RE providers and customer requirements.
We developed a model to improve semantic matching results by using instances in the domain of RE.
Our model consists three stages as follow: (1) Extracting instances of RE providers (2) Extracting instances of customer requirements (3) Matching process among both extracted instances.
The matching process has done by using semantic similarity measure.
This model suggests an appropriate RE providers that meets customer requirements.
Also during our study, we collected many documents and reports that discussed RE providers and consumer quires to collection their data related to each of them.
Then convert these data into text file in order to extract their instances.
The proposed model is evaluated by comparing the results of our approach with the results of traditional approaches.
The experiments have conducted in order to check the efficiency of the proposed model.
However, the results demonstrated that using instances reduced the error to (10%).
Main Subjects
Information Technology and Computer Science
No. of Pages
148
Table of Contents
Table of contents.
Abstract.
Abstract in Arabic.
Chapter One : Introduction.
Chapter Two : Literature review and related works.
Chapter Three : Renewable energy ontology and similarity measures.
Chapter Four : Methodology and proposed model.
Chapter Five : Experimental results.
Chapter Six : Conclusion and future work.
References.
American Psychological Association (APA)
Ahmad, Saddam Hamdan. (2014). Extracting instances to improve semantic matching in the domain of renewable energy. (Master's theses Theses and Dissertations Master). Middle East University, Jordan
https://search.emarefa.net/detail/BIM-694638
Modern Language Association (MLA)
Ahmad, Saddam Hamdan. Extracting instances to improve semantic matching in the domain of renewable energy. (Master's theses Theses and Dissertations Master). Middle East University. (2014).
https://search.emarefa.net/detail/BIM-694638
American Medical Association (AMA)
Ahmad, Saddam Hamdan. (2014). Extracting instances to improve semantic matching in the domain of renewable energy. (Master's theses Theses and Dissertations Master). Middle East University, Jordan
https://search.emarefa.net/detail/BIM-694638
Language
English
Data Type
Arab Theses
Record ID
BIM-694638
