Extraction of taxonomic relations from Arabic text for ontology construction
Other Title(s)
استخلاص العلاقات التصنيفية من النص العربي لغرض بناء الأنطولوجيا
Dissertant
Thesis advisor
University
Islamic University
Faculty
Faculty of Information Technology
Department
Information Technology
University Country
Palestine (Gaza Strip)
Degree
Master
Degree Date
2016
English Abstract
The huge amount of textual information available electronically has made it difficult for many users to search and find the right information within acceptable time.
The ontology based techniques can contribute to solve these problems and help users in exploiting these vast resources.
Ontology could be an efficient way to improve the process of searching and exploiting information on the web.
The benefit of ontology is that it provides a standard for the vocabulary used in a specific domain and relations.
This thesis proposes a method to extract taxonomic relations to construct ontology automatically from natural Arabic text on Political News domain using four stages.
First perform pre-processing operations in text such as tokenization, normalization and stop-word removing and then morphological information in pre-processing is extracted to detect the part of speech of each word.
Second extraction of terms by integration between lexical resources and machine-learning classifier for Arabic named entities recognition.
Third extraction of taxonomic relations between terms using rule based domain.
Finally constructing a set of transformation rules to identify the appropriate ontological elements from the terms and taxonomic relations that extracted.
After constructing the ontology, we build RDF language to represent information about resources on the text and build ontology with class-subclass relations and property relations.
Two methods are performed to test and evaluate the accuracy of approach, first using measures calculate precision, recall and f-measure.
Second using a reasoner to check the consistency.
The results shows satisfactory results for all terms and taxonomic relations extraction, with precision = 92% and recall = 91%.
Main Subjects
Information Technology and Computer Science
No. of Pages
106
Table of Contents
Table of contents.
Abstract.
Abstract in Arabic.
Chapter One : Introduction.
Chapter Two : Theoretical and technical foundation.
Chapter Three : Related works.
Chapter Four : Automatically constructing domain ontology from Arabic text.
Chapter Five : Implementation.
Chapter Six : Experimental results and evaluation.
Chapter Seven : Conclusions and future work.
References.
American Psychological Association (APA)
al-Zurayi, Basil Salamah. (2016). Extraction of taxonomic relations from Arabic text for ontology construction. (Master's theses Theses and Dissertations Master). Islamic University, Palestine (Gaza Strip)
https://search.emarefa.net/detail/BIM-727253
Modern Language Association (MLA)
al-Zurayi, Basil Salamah. Extraction of taxonomic relations from Arabic text for ontology construction. (Master's theses Theses and Dissertations Master). Islamic University. (2016).
https://search.emarefa.net/detail/BIM-727253
American Medical Association (AMA)
al-Zurayi, Basil Salamah. (2016). Extraction of taxonomic relations from Arabic text for ontology construction. (Master's theses Theses and Dissertations Master). Islamic University, Palestine (Gaza Strip)
https://search.emarefa.net/detail/BIM-727253
Language
English
Data Type
Arab Theses
Record ID
BIM-727253
