Feature-based opinion summarization for Arabic reviews
Other Title(s)
تلخيص الآراء للتقييمات العربية بناء على الميزة
Dissertant
Thesis advisor
University
Islamic University
Faculty
Faculty of Information Technology
Department
Information Technology
University Country
Palestine (Gaza Strip)
Degree
Master
Degree Date
2017
English Abstract
Opinion mining applications work with a large number of opinion holders.
This means a summary of opinions is important so we can easily interpret holders' opinions.
The aim of this paper is to provide a feature-based summarization for Arabic reviews.
In our work, a system is proposed using Natural Language Processing (NLP) techniques, information extraction and sentiment lexicons.
This provides users to access the opinions expressed in hundreds of reviews in a concise and useful manner.
We start with extracting feature for a specific domain, assigned sentiment classification to each feature, and then summarized the reviews.
We conducted a set of experiments to evaluate our system using data corpus from the hotel domain.
The accuracy for opinion mining we calculated using objective evaluation was 71.22%.
We, also, applied subjective evaluation for the summary generation and it indicated that our system achieved a relevant measure of 73.23 % accuracy for positive summary and 72.46% accuracy for a negative summary.
Main Subjects
Information Technology and Computer Science
No. of Pages
59
Table of Contents
Table of contents.
Abstract.
Abstract in Arabic.
Chapter One : Introduction.
Chapter Two : Theoretical background.
Chapter Three : Literature review.
Chapter Four : Methodology.
Chapter Five : Experiments and results.
Chapter Six : Conclusion and future work.
References.
American Psychological Association (APA)
Salih, Dua Isa Muhammad. (2017). Feature-based opinion summarization for Arabic reviews. (Master's theses Theses and Dissertations Master). Islamic University, Palestine (Gaza Strip)
https://search.emarefa.net/detail/BIM-905422
Modern Language Association (MLA)
Salih, Dua Isa Muhammad. Feature-based opinion summarization for Arabic reviews. (Master's theses Theses and Dissertations Master). Islamic University. (2017).
https://search.emarefa.net/detail/BIM-905422
American Medical Association (AMA)
Salih, Dua Isa Muhammad. (2017). Feature-based opinion summarization for Arabic reviews. (Master's theses Theses and Dissertations Master). Islamic University, Palestine (Gaza Strip)
https://search.emarefa.net/detail/BIM-905422
Language
English
Data Type
Arab Theses
Record ID
BIM-905422
