A framework for semantic knowledge representation of Al-Quran based on word dependencies
A variety of applications have been built in recent years with the aim to extract knowledge from Al-Quran. Current knowledge representations of Al-Quran give attention primarily on conceptual ontology models that describe the semantic relations between the Quranic concepts or entities. There se...
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| Main Authors: | , , , , , , , |
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| Format: | Proceeding Paper |
| Language: | en en |
| Published: |
IEEE
2021
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/120802/7/120802_A%20framework%20for%20semantic%20knowledge.pdf http://irep.iium.edu.my/120802/8/120802_A%20framework%20for%20semantic%20knowledge_Scopus.pdf http://irep.iium.edu.my/120802/ https://ieeexplore.ieee.org/abstract/document/9497925 https://doi.org/10.1109/CAMP51653.2021.9497925 |
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| Summary: | A variety of applications have been built in
recent years with the aim to extract knowledge from Al-Quran.
Current knowledge representations of Al-Quran give attention
primarily on conceptual ontology models that describe the
semantic relations between the Quranic concepts or entities.
There seems to be minimal effort towards recognizing the
semantic relations between words in Quranic text, which is
relatively more complex. This paper aims to present a
framework for semantic knowledge representation of AlQuran using dependency relations between words, in an
attempt to boost the retrieval accuracy for Al-Quran. The
semantic analysis is performed on Quranic verses according to
word dependency relations using dependency parsing. Based
on parsed dependencies, a set of rules are formulated to build a
semantic graph of Surah Ali Imran of Al-Quran. The efficiency
of the semantic representation was tested by developing a
prototype question answering system. The framework was
evaluated using precision and recall, First Hit Success, First
Answer Reciprocal Rank and Total Reciprocal Rank by
comparing the retrieved and actual answers. The results
indicate that the performance of the proposed framework
using word dependencies improves the semantic representation
of knowledge. |
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