Comparison of ontology learning techniques for Qur’anic text
Currently, ontology plays an important role in semantic Web technology and defines the concepts and relationships among these concepts. Ontology learning approach is to distinguish according to the type of input such as text, dictionary, knowledge, policies, schemes and schemes of semi-structured re...
محفوظ في:
| المؤلف الرئيسي: | |
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| التنسيق: | أطروحة |
| اللغة: | English |
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2010
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| الوصول للمادة أونلاين: | http://eprints.utm.my/id/eprint/11067/1/ChewKimMeyMFSKSM2010.pdf |
| الوسوم: |
إضافة وسم
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my-utm-ep.110672018-05-30T02:32:48Z Comparison of ontology learning techniques for Qur’anic text 2010-04 Chew, Kim Mey QA75 Electronic computers. Computer science Currently, ontology plays an important role in semantic Web technology and defines the concepts and relationships among these concepts. Ontology learning approach is to distinguish according to the type of input such as text, dictionary, knowledge, policies, schemes and schemes of semi-structured relations. Ontology learning can be explained as extract information subtask and ontology learning objectives is to dig the relevant concepts and relationships from the corpus or a particular type of data sets. In this project, I will focus on ontology learning from text using Qur’anic text as input data. The approaches which used to extract Qur’anic text in this project are Alfonseca and Manandhar’s method and Gupta and Colleagues’s approach. After completed the project, I hope to exit with an appropriate method or technique which suitable to extract the ontologies from Qur’anic text. With this ontology extraction tool, I hope can help more people to understand the true meaning of this language and teach the Qur'an. 2010-04 Thesis http://eprints.utm.my/id/eprint/11067/ http://eprints.utm.my/id/eprint/11067/1/ChewKimMeyMFSKSM2010.pdf application/pdf en public masters Universiti Teknologi Malaysia, Faculty of Computer Science and Information Systems Faculty of Computer Science and Information System |
| institution |
Universiti Teknologi Malaysia |
| collection |
UTM Institutional Repository |
| language |
English |
| topic |
QA75 Electronic computers Computer science |
| spellingShingle |
QA75 Electronic computers Computer science Chew, Kim Mey Comparison of ontology learning techniques for Qur’anic text |
| description |
Currently, ontology plays an important role in semantic Web technology and defines the concepts and relationships among these concepts. Ontology learning approach is to distinguish according to the type of input such as text, dictionary, knowledge, policies, schemes and schemes of semi-structured relations. Ontology learning can be explained as extract information subtask and ontology learning objectives is to dig the relevant concepts and relationships from the corpus or a particular type of data sets. In this project, I will focus on ontology learning from text using Qur’anic text as input data. The approaches which used to extract Qur’anic text in this project are Alfonseca and Manandhar’s method and Gupta and Colleagues’s approach. After completed the project, I hope to exit with an appropriate method or technique which suitable to extract the ontologies from Qur’anic text. With this ontology extraction tool, I hope can help more people to understand the true meaning of this language and teach the Qur'an. |
| format |
Thesis |
| qualification_level |
Master's degree |
| author |
Chew, Kim Mey |
| author_facet |
Chew, Kim Mey |
| author_sort |
Chew, Kim Mey |
| title |
Comparison of ontology learning techniques for Qur’anic text |
| title_short |
Comparison of ontology learning techniques for Qur’anic text |
| title_full |
Comparison of ontology learning techniques for Qur’anic text |
| title_fullStr |
Comparison of ontology learning techniques for Qur’anic text |
| title_full_unstemmed |
Comparison of ontology learning techniques for Qur’anic text |
| title_sort |
comparison of ontology learning techniques for qur’anic text |
| granting_institution |
Universiti Teknologi Malaysia, Faculty of Computer Science and Information Systems |
| granting_department |
Faculty of Computer Science and Information System |
| publishDate |
2010 |
| url |
http://eprints.utm.my/id/eprint/11067/1/ChewKimMeyMFSKSM2010.pdf |
| _version_ |
1747814804991508480 |