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...

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主要作者: Chew, Kim Mey
格式: Thesis
語言:English
出版: 2010
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在線閱讀:http://eprints.utm.my/id/eprint/11067/1/ChewKimMeyMFSKSM2010.pdf
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總結: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.