864 research outputs found

    Arabic Quranic Search Tool Based on Ontology

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    This paper reviews and classifies most of the common types of search techniques that have been applied on the Holy Quran. Then, it addresses the limitations of these methods. Additionally, this paper surveys most existing Quranic ontologies and what are their deficiencies. Finally, it explains a new search tool called: a semantic search tool for Al-Quran based on Qur’anic on-tologies. This tool will overcome all limitations in the existing Quranic search applications

    Quranic Arabic Semantic Search Model Based on Ontology of Concepts

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    The Holy Quran is the essential resource for Islamic sciences and Arabic language. Therefore, numerous Quranic search applications have been built to facilitate the retrieval of knowledge from the Quran. This thesis presents a novel Arabic Quran semantic search model. First, this thesis evaluated existing search tools constructed for the Holy Quran, against 13 criteria depending on: search features, output features, the precision of the retrieved verses, recall database size, and types of database contents. Then, the study reviewed the existing Quran ontologies and compared them against 11 criteria. Some deficits have been found in all these ontologies. Additionally, a single Quranic ontology does not cover most of the knowledge in the Quran. Therefore, I developed a new Arabic-English Quran ontology from ten datasets related to the Quran such as: Quran chapter and verse names, Quran word meanings, and Quran topics. The main aim of developing a Quranic ontology is to facilitate the retrieval of knowledge from the Quran. Additionally, the Quran ontology will enrich the raw Arabic and English Quran text with Islamic semantic tags. Furthermore, I developed the first Annotated Corpus of Quran Questions and Answers in Arabic. This corpus has 2200 pairs of question and answer collected from trusted Islamic sources. Each pair of question and answer is labelled with 5 tags. Examples of tags are: question type: either factoid or descriptive, topic of question-based on the Quran ontology, and question class. Finally, the thesis explains a new semantic search model for the Arabic Quran based on my Quran ontology. This model aims at overcoming limitations in the existing Quran search applications. This search tool employs both Information Retrieval techniques and semantic search technologies. The performance of this search model is evaluated by using The Annotated Corpus of Arabic Quran Questions and Answers

    Building Quranic stories ontology using MappingMaster domain-specific language

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    The Holy Quran, due to it is full of many inspiring stories and multiple lessons that need to understand it requires additional attention when it comes to searching issues and information retrieval. Many works were carried out in the Holy Quran field, but some of these dealt with a part of the Quran or covered it in general, and some of them did not support semantic research techniques and the possibility of understanding the Quranic knowledge by the people and computers. As for others, techniques of data analysis, processing, and ontology were adopted, which led to directed these to linguistic aspects more than semantic. Another weakness in the previous works, they have adopted the method manually entering ontology, which is costly and time-consuming. In this paper, we constructed the ontology of Quranic stories. This ontology depended in its construction on the MappingMaster domain-specific language (MappingMaster DSL)technology, through which concepts and individuals can be created and linked automatically to the ontology from Excel sheets. The conceptual structure was built using the object role modeling (ORM) modeling language. SPARQL query language used to test and evaluate the propsed ontology by asking many competency questions and as a result, the ontology answered all these questions well

    Extracting semantic relations from the Quranic Arabic based on Arabic conjunctive patterns

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    © 2017 The Authors There is an immense need for information systems that rely on Arabic Quranic ontologies to provide a precise and comprehensive knowledge to the world. Since semantic relations are a vital component in any ontology and many applications in Natural Language Processing strongly depend on them, this motivates the development of our approach to extract semantic relations from the Quranic Arabic Corpus, written in Arabic script, and enrich the automatic construction of Quran ontology. We focus on semantic relations resulting from proposed conjunctive patterns which include two terms with the conjunctive AND enclosed in between. The strength of each relation is measured based on the correlation coefficient. Finally, we evaluate the significance of this method by using hypotheses testing and Student t-test. The obtained results are very promising since we combine an accurate Arabic grammar with strong statistical techniques to prove the existence and measure the strength of this type of semantic relations

    Semantic-based Ontology for Malay Qur'an Reader

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    The Quran has been translated into various languages around the world by Muslim experts. One of them is in Malay. There are numerous applications built to facilitate the retrieval of knowledge from the Malay Qur’an. However, there are limited resources and tools that are available or made accessible for the research on Malay Qur’an. Furthermore, there are several issues that need to be considered when dealing with Malay Qur’an translation; such as ambiguities of words, lack of equivalence words between Malay and English or Malay and Arabic, and different structures of word, sentence, and discourse in these two languages. Therefore, this research summarizes the search techniques used in existing research on Qur’an. Moreover, this paper also studied the previous research conducted on Qur’an Semantic Search and Quran Ontology-Based Search focusing on Malay Qur’an. This review helps the research in addressing the general problems and limitations in Malay Qur’an that influence its accessibility. This research proposed the research framework for new semantic based ontology for Malay Qur’an. The final outcome will be an accessible tool that can help a Malay reader to understand the Qur’an in better ways

    A Review of Semantic Search Methods to Retrieve Information from the Qur’an Corpus

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    The Holy Qur’an is the most important resource for the Islamic sciences and the Arabic language (Iqbal et al., 2013). Muslims believe that the Qur’an is a revelation from Allah that was given 1,356 years ago. The Qur’an contains about 80,000 words divided into 114 chapters (Atwell et al., 2011). A chapter consists of a varying number of verses. This holy book contains information on diverse topics, such as life and the history of humanity and scientific knowledge (Alrehaili and Atwell, 2014). Corpus linguistics methods can be applied to study the lexical patterns in the Qur’an; for example, the Qur’an is one of the corpora available on the SketchEngine website. Qur’an researchers may want to go beyond word patterns to search for specific concepts and information. As a result, many Qur’anic search applications have been built to facilitate the retrieval of information from the Qur’an. Examples of these web applications are Qurany (Abbas, 2009), Qur’an Explorer (Explorer, 2005), Tanzil (Zarrabi-Zadeh, 2007), Qur’anic Arabic corpus (Dukes, 2013), and Quran.com. The techniques used to retrieve information from the Qur’an can be classified into two types: semantic-based and keyword-based. Semantic-based search techniques are concept-based which retrieves results by matching the contextual meaning of terms as they appear in a user’s query, whereas the keyword-based search technique returns results according to the letters in the word(s) of a query (Sudeepthi et al., 2012). The majority of Qur’anic search tools employ the keyword search technique. The existing Qur’anic semantic search techniques include the ontology-based technique (concepts) (Yauri et al., 2013), the synonyms-set technique (Shoaib et al., 2009), and the cross language information retrieval (CLIR) technique (Yunus et al., 2010). The ontology-based technique searches for the concept(s) matching a user’s query and then returns the verses related to these concept(s). The synonyms-set method produces all synonyms of the query word using WordNet and then returns all Qur’anic verses that contain words matching any synonyms of the query word. Cross language information retrieval (CLIR) translates the words of an input query into another language and then retrieves verses that contain words matching the translated words. On the other hand, keyword-based techniques include keyword matching, the morphologically-based technique (Al Gharaibeh et al., 2011), and use of a Chabot (Abu Shawar and Atwell, 2004). The keyword matching method returns verses that contain any of the query words. The morphologically-based technique uses stems of query words to search in the Qur’an corpus. In other words, this technique generates all other forms of the query words and then finds all Qur’anic verses matching those word forms. The Chabot selects the most important words such as nouns or verbs from a user query and then returns the Qur’anic verses that contain any words matching the selected words. There are several deficiencies with the Qur’anic verses (Aya’at) retrieved for a query using the existing keyword search technique. These problems include the following: some irrelevant verses are retrieved, some relevant verses are not retrieved, or the sequence of retrieved verses is not in the right order (Shoaib et al., 2009). Misunderstanding the exact meaning of input words forming a query and neglecting some theories of information retrieval contribute significantly to limitations in the keyword-based technique (Raza et al.). Additionally, Qur’anic keyword search tools use limited Islamic resources related to the Qur’an. This affects the accuracy of the retrieved results. Moreover, current Qur’anic semantic search techniques have limitations in retrieved results. The main causes of these limitations include the following: semantic search tools use one source of Qur’anic ontology that does not cover all concepts in the Holy Qur’an, and Qur’anic ontologies are not aligned to each other, leading to inaccurate and uncomprehensive resources for Qur’anic ontology. To overcome the limitations in both semantic and keyword search techniques, we designed a framework for a new semantic search tool called the Qur’anic Semantic Search Tool (QSST). This search tool aims to employ both text-based and semantic search techniques. QSST aligns the existing Quranic ontologies to reduce the ambiguity in the search results. QSST can be divided into four components: a natural language analyser (NLA), a semantic search model (SSM), a keywords search model (KSM), and a scoring and ranking model (SRM). NLA tokenizes a user’s query and then applies different natural language processing techniques to the tokenized query. These techniques are the following: spelling correction, stop word removal, stemming, and part of speech tagging (POS). After that, the NLA uses WordNet to generate synonyms for the reformatted query words and sends these synonyms to the SSM and the KSM. The SSM searches in the Qur’anic Ontology database to find the related concepts of the normalised query and then returns results. At the same time, KSM retrieves results based on words matching the input words. SRM refines the results retrieved from both KSM and SSM by eliminating the redundant verses. Next, SRM ranks and scores the refined results. Finally, SRM presents the results to the user. References Abbas, N. H. 2009. Quran 'search for a concept' tool and website. MRes thesis, University of Leeds. Abu Shawar, B. and Atwell, E. 2004. An Arabic chatbot giving answers from the Qur'an. Proceedings of TALN. 4(2), pp.197-202. Al Gharaibeh, A. et al. 2011. The usage of formal methods in Quran search system. In: Proceedings of international conference on information and communication systems, Ibrid, Jordan. pp.22-24. Alrehaili, S. M. and Atwell, E. 2014. Computational ontologies for semantic tagging of the Quran: A survey of past approaches. In: LREC 2014 Proceedings. Atwell, E. et al. 2011. An artificial intelligence approach to Arabic and Islamic content on the internet. In: Proceedings of NITS 3rd National Information Technology Symposium. Dukes, K. 2013. Statistical parsing by machine learning from a classical Arabic treebank. PhD thesis. Explorer, Q. 2005. Quran Explorer [Online]. [Accessed 26 October 2014]. Available from: http://www.quranexplorer.com/Search/Default.aspx Iqbal, R. et al. 2013. An experience of developing Quran ontology with contextual information support. Multicultural Education & Technology Journal. 7, pp.333-343. Raza, S.A. et al. An essential framework for concept based evolutionary Quranic search engine (CEQSE). Shoaib, M. et al. 2009. Relational WordNet model for semantic search in Holy Quran. Emerging Technologies, 2009. ICET 2009. International Conference on, 2009. IEEE, 29-34. Sudeepthi, G. et al. 2012. A survey on semantic web search engine. International Journal of Computer Science, 9. Yauri, A. R. et al. 2013. Quranic verse extraction based on concepts using OWL-DL ontology. Research Journal of Applied Sciences Engineering and Technology. 6, pp.4492-4498. Yunus, M. et al. 2010. Semantic query for Quran documents results. Open Systems (ICOS), 2010 IEEE Conference on, 2010. IEEE, 1-5. Zarrabi-Zadeh, H. 2007. Tanzil [Online]. [Accessed 26 October 2014]. Available from: http://tanzil.net

    Parallel corpus multi stream question answering with applications to the Qu'ran

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    Question-Answering (QA) is an important research area, which is concerned with developing an automated process that answers questions posed by humans in a natural language. QA is a shared task for the Information Retrieval (IR), Information Extraction (IE), and Natural Language Processing communities (NLP). A technical review of different QA system models and methodologies reveals that a typical QA system consists of different components to accept a natural language question from a user and deliver its answer(s) back to the user. Existing systems have been usually aimed at structured/ unstructured data collected from everyday English text, i.e. text collected from television programmes, news wires, conversations, novels and other similar genres. Despite all up-to-date research in the subject area, a notable fact is that none of the existing QA Systems has been tested on a Parallel Corpus of religious text with the aim of question answering. Religious text has peculiar characteristics and features which make it more challenging for traditional QA methods than other kinds of text. This thesis proposes PARMS (Parallel Corpus Multi Stream) Methodology; a novel method applying existing advanced IR (Information Retrieval) techniques, and combining them with NLP (Natural Language Processing) methods and additional semantic knowledge to implement QA (Question Answering) for a parallel corpus. A parallel Corpus involves use of multiple forms of the same corpus where each form differs from others in a certain aspect, e.g. translations of a scripture from one language to another by different translators. Additional semantic knowledge can be referred as a stream of information related to a corpus. PARMS uses Multiple Streams of semantic knowledge including a general ontology (WordNet) and domain-specific ontologies (QurTerms, QurAna, QurSim). This additional knowledge has been used in embedded form for Query Expansion, Corpus Enrichment and Answer Ranking. The PARMS Methodology has wider applications. This thesis applies it to the Quran – the core text of Islam; as a first case study. The PARMS Method uses parallel corpus comprising ten different English translations of the Quran. An individual Quranic verse is treated as an answer to questions asked in a natural language, English. This thesis also implements PARMS QA Application as a proof of concept for the PARMS methodology. The PARMS Methodology aims to evaluate the range of semantic knowledge streams separately and in combination; and also to evaluate alternative subsets of the DATA source: QA from one stream vs. parallel corpus. Results show that use of Parallel Corpus and Multiple Streams of semantic knowledge have obvious advantages. To the best of my knowledge, this method is developed for the first time and it is expected to be a benchmark for further research area

    A Hybrid-based Term Extraction method on the Arabic text of the Qur'an

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    The identification of relevant domain terms is a crucial step in numerous natural language processing applications. Term Extraction is a process of obtaining a set of terms that represent the domain of a given text. The majority of Term Extraction research projects conducted for the Qur’an have used translated text instead of the original text of the Qur’an. The extraction of terms from the original Arabic text rather than a translation may help in retrieving more relevant terms, due to the lack of Islamic equivalence of some Quranic terms in other languages. This paper demonstrates a hybridbased method for the acquisition of a list of domain-specific terms from the Arabic text of the Quran. The produced list of terms validated a common evaluation for ranked list; precision of up to 0.81 was achieved for the top 200 terms. We discussed the low precision that was achieved, in the context of evaluate the result against two existing datasets from previous research

    Al-Quran ontology based on knowledge themes

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    Islamic knowledge is gathered through the understanding the Al-Quran.It requires ontology which can capture the knowledge and present it in a machine readable structured However, current ontology approaches is irrelevant and inaccuracy in producing true concepts of Al-Quran knowledge, because it used traditional methods that only define the concepts of knowledge without connecting to a related theme of knowledge.The themes of knowledge are important to provide true meaning and explanation of Al-Quran knowledge classification.The main aims of this paper are to demonstrate the development of ontology Al-Quran and method used for searching the Al-Quran knowledge using the semantic search approach. Expert review has been applied to validate the ontology model and evaluate the relevance and precision of searching results
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