Presentation on theme: "Quranic Arabic Corpus Data Mining & Text Analytics By Ismail Teladia & Abdullah Alazwari."— Presentation transcript:
Quranic Arabic Corpus Data Mining & Text Analytics By Ismail Teladia & Abdullah Alazwari
Introduction What is the Quran ? Holy book for Muslims Revealed from 610 AD 6,236 verses, 114 chapters Corpus Definition. Written or spoken language What is the Quranic Arabic Corpus ? 77,430 words of Quranic Arabic Researcher: Kais Dukes
Features of QAC: Morphological Annotation Syntactic Treebank Semantic Ontology
Morphological Annotation Word By Word Grammar Syntax Morphology Part-of-speech tagging Natural Language Computing Technology
Details of Word’s Grammar Clicking the word gives more detail: Type of Word Translation Gender Case Root In addition it shows the verse in which word appears and sound recitation of the verse.
Syntactic Treebank Verse by verse dependency graphs Meaning of verse (broken down) Sentence structure (dependencies) Case Mathematical graph theory
Ontology of Concepts Knowledge representation Relationship between concepts Historic places and people Named entity tagging E.g. Sun, Moon, Star, Earth classified under “Astronomical Body” Uses predicate logic
Visual Representation of Ontology 300 linked concepts with 350 relations
Conclusion Uses of the QAC: Analysing Arabic text of each verse Linking Arabic words through dependencies Finding relationships between concepts Website used daily by 2,500 people from 165 countries
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