عنوان

An Automatic Similarity Detection Engine Between Sacred Texts Using Text Mining and Similarity Measures

Number

TL48047

.Language of Text, Soundtrack etc

انگلیسی

Title Proper

An Automatic Similarity Detection Engine Between Sacred Texts Using Text Mining and Similarity Measures

General Material Designation

[Thesis]

General Material Designation

[Thesis]

General Material Designation

[Thesis]

General Material Designation

[Thesis]

First Statement of Responsibility

Salha Hassan Muhammed Qahl

Subsequent Statement of Responsibility

Fokoue, Ernest

Name of Publisher, Distributor, etc.

Rochester Institute of Technology

Date of Publication, Distribution, etc.

2014

Specific Material Designation and Extent of Item

104

Text of Note

Committee members: Chen, Linlin; Parody, Robert

Text of Note

Place of publication: United States, Ann Arbor; ISBN=978-1-321-40085-4

Dissertation or thesis details and type of degree

M.S.

Discipline of degree

Applied Statistics

Body granting the degree

Rochester Institute of Technology

Text preceding or following the note

2014

Text of Note

Is there any similarity between the contexts of the Holy Bible and the Holy Quran, and can this be proven mathematically? The purpose of this research is using the Bible and the Quran as our corpus, we explore the performance of various feature extraction and machine learning techniques. The unstructured nature of text data adds an extra layer of complexity in the feature extraction task, and the inherently sparse nature of the corresponding data matrices makes text mining a distinctly difficult task. Among other things, We assess the difference between domain-based syntactic feature extraction and domain-free feature extraction, and then use a variety of similarity measures like Euclidean, Hillinger, Manhattan, cosine, Bhattacharyya, symmetries kullback-leibler, Jensen Shannon, probabilistic chi-square and clark. For a similarity to identify similarities and differences between sacred texts.

Mathematics; Statistics; Computer science

Subject Term

Pure sciences;Applied sciences;Data mining;Machine learning;Sacred texts;Similarity measures

Sookdial, Vijay T.

Fokoue, Ernest

Subdivision

Applied Statistics

Rochester Institute of Technology

Call Number

1641125320; 1570850

Electronic name

p

[Thesis]

276903

a

Y