Sentences ordering approach for multi-document summarization in domain specific text document
Other Title(s)
تلخيص الوثائق المتعددة و ترتيب الجمل في مجال نصوص الوثائق
Dissertant
Thesis advisor
Comitee Members
University
Amman Arab University
Faculty
Collage of Computer Sciences and Informatics
Department
Department of Computer Science
University Country
Jordan
Degree
Master
Degree Date
2016
English Abstract
In this thesis, three approach techniques are presented to produce sentence ordering summarization involving a novel graph summarization.
The 1st approach we applied the normalized importance score (TF-IDF threshold (tf =0.0) of sentence to compute based on different semantic similarity measure and semantic features (with cosine -normal, 0.4- train) to choose sentences with the most representation in the document.
Stack decoder algorithm (with summary length=100, sentence length=6) was used as a model and builds on it to create the summaries nearest to original document.
The 2nd approach the sentences are clustering based on (K-means clustering) semantic similarity score and selection that represent from all cluster that is involved in the created summary.
The 3rd approach is a novel graph formulation (with threshold=0.5) where it is generated on cliques found in the organized graph.
Graph is created to build the edges among sentences that have similar topics but not similar as semantically.
Linear combination of feature value is used as our importance function.
By training on DUC2002 data we calculate the weight for the feature value and apply them to get the score of the important sentence in the test data.
We apply this approach to produce 100 word summaries of a dataset available as part of DUC 2004 and discus the development of the system, analysis and algorithm.
Rouge score is used for performance evaluation of the system.
Main Subjects
Information Technology and Computer Science
No. of Pages
95
Table of Contents
Table of contents.
Abstract.
Abstract in Arabic.
Chapter One : General framework of the thesis.
Chapter Two : Related work.
Chapter Three : General framework of automatic summarization.
Chapter Four : Summarization methodology.
Chapter Five : Experiment and evaluation.
Chapter Six : Conclusion and future work.
References.
American Psychological Association (APA)
al-Nuaymi, Hamid Ali Husayn. (2016). Sentences ordering approach for multi-document summarization in domain specific text document. (Master's theses Theses and Dissertations Master). Amman Arab University, Jordan
https://search.emarefa.net/detail/BIM-722658
Modern Language Association (MLA)
al-Nuaymi, Hamid Ali Husayn. Sentences ordering approach for multi-document summarization in domain specific text document. (Master's theses Theses and Dissertations Master). Amman Arab University. (2016).
https://search.emarefa.net/detail/BIM-722658
American Medical Association (AMA)
al-Nuaymi, Hamid Ali Husayn. (2016). Sentences ordering approach for multi-document summarization in domain specific text document. (Master's theses Theses and Dissertations Master). Amman Arab University, Jordan
https://search.emarefa.net/detail/BIM-722658
Language
English
Data Type
Arab Theses
Record ID
BIM-722658
