CONCEPTUALISATION OF DEATH AND RESURRECTION IN THE HOLY QURAN: A COGNITIVE-SEMANTIC APPROACH

Conceptual metaphor is the discursive linguistic strategy employed in the Holy Quran to imprint upon the human mind the Quranic worldview. This approach can better explain the abstract concepts of death and resurrection in the Holy Quran through cross domain mapping with human experiential concepts. Traditional exegetes and rhetoricians missed this phenomenon in the Holy Quran because of their preoccupation with rhetorical and theological aspects of death and resurrection. The existing cognitive semantic research has also paid little or no attention to the investigation of death and resurrection in the Holy Quran. Therefore, this paper attempts to investigate the conceptual metaphor themes of death and resurrection in the Holy Quran. Data were retrieved from the Holy Quran on the basis of key words and phrases encapsulating the abstract concepts of death and resurrection. The analysis of data reveals various conceptual metaphor themes. It is also found that the data question the asymmetrical hypothesis of conceptual metaphor theory and its role as a sole model of metaphor interpretation. This study is part of the growing research on conceptual metaphor in the Holy Quran and is hoped to contribute to further research on the cognitive semantic analysis of the Holy Quran.  Keywords: cognition, cognitive-semantic, conceptual metaphor, experiential gestalt, QuranCite as: Khan, S. & Ali, R. (2016). Conceptualisation of death and resurrection in the holy Quran: A cognitive-semantic approach. Journal of Nusantara Studies, 1(2), 11-24.  http://dx.doi.org/10.24200/jonus.vol1iss2pp11-2

Knowledge exploration: selected works on Quran ontology development

This paper presents key features and challenges ahead for the development and knowledge retrieval of Quran ontology. Recent studies have made significant advances towards the development of Quran ontology. In the recent past, there have been numerous studies conducted on the application of semantic technologies on Quran. Contribution of this paper is its focus on finding the direction of knowledge exploration in Quran. Several studies on Quran ontology development help us in analyzing its linguistic features. Another dimension where Quran excels is the Knowledge of it. There are few studies that concentrate on retrieval of knowledge from Quran. In this literature review, we have included studies that can help us in developing semantic application for knowledge exploration from Quran. This paper devises challenges mainly focusing towards exploration of knowledge in the Quran and summaries research in this area, discuss key features and open research issues

An application of distributional semantics for the analysis of the Holy Quran

In this contribution we illustrate the methodology and the results of an experiment we conducted by applying Distributional Semantics Models to the analysis of the Holy Quran. Our aim was to gather information on the potential differences in meanings that the same words might take on when used in Modern Standard Arabic w.r.t. their usage in the Quran. To do so we used the Penn Arabic Treebank as a contrastive corpu

Quranic-based concepts: verse relations extraction using Manchester OWL syntax

In recent years, there is global demand for Islamic knowledge by both Muslims and non-Muslims. This has brought about number of automated applications that ease the retrieval of knowledge from the holy books. However current retrieval methods lack semantic information they are mostly base on keywords matching approach. In this paper we have proposed a Model that will make use of semantic Web technologies (ontology) to model Quran domain knowledge. The system will enhance Quran knowledge by enabling queries in natural language

TRANSLATION UNIT IN THE TRANSLATION OF AL-QURAN INTO INDONESIAN

Translation of Al-Qur’an is considered very specific because Al-Qur’an is sacred text which is believed to be a Holy Scripture that is revealed as a guide for religious and social life. This article is based on consideration on translation of Al-Qur’an into Indonesia. Vinay and Darbelnet’s theory of direct and oblique translation is one of theories considered to be applied in this article. Other theory which is also involved in the analysis in this article is Bassnett and Lafevere’s theory which claims that the basic UT can be the culture of the involved languages. While Al-Quran uses al-hija’iyah alphabe

ON FEATURE EXTRACTION FOR ENGLISH HOLY QURAN TAFSEER TEXT CLASSIFICATION

Numerous previous works classified text corpus by topic, sentiment, genre, or author. This investigates a different case of text corpus. The corpus is the tafseer of Holy Quran verses by Al-Jalalayn. Holy Quran dataset is selected as the corpus for this study because of its content which sometimes is difficult to separate even by human judge. The number of distinctive words is small, but the number of noise words is relatively high. The challenge of classifying the Holy Quran is that there are verses that have implicit meaning. To overcome the lack of ability to recognize implicit meaning in the text, WordNet Thesaurus is used to perform a semantic similarity approach. In this research, several processes to classify a document were performed, which were pre-processing, feature extraction, semantic weighting, classifier training, and evaluation. During feature extraction, produced several features as follows: Term Frequency (TF), Term Frequency–Inverse Document Frequency (TF-IDF), Part-of-Speech Tagging (POSTAG), and Bigram. The proposed method is performing weight calculation called Document-to-Class semantic similarity. The new measure used in the semantic similarity calculation was a combination of the Wu and Palmer (WUP) method and shortest path semantic similarity method with minor modifications. This was followed with classifier training, where the classification process using a Modified Multinomial Naive-Bayes classifier were performed. The proposed method is to modify the likelihood probability by using a weighted value from a prior process called document-to-class semantic similarity. During evaluation process, we evaluated the classifier performance using the Holy Quran dataset we created. For comparation, we also used an Amazon review dataset, a Yelp review dataset, and an IMDB review dataset. The measures used in the evaluation process were Accuracy, Precision, Recall, and F1-Measure. The F1-Measures for the Holy Quran dataset using feature combination POSTAG, BIGRAM and TF was 60.5 %. The F1 score for combination POSTAG, BIGRAM and TFIDF was 58.6% and The F1 score for combination POSTAG, BIGRAM and proposed Weighted TF 66.4%

New instances classification framework on Quran ontology applied to question answering system

Instances classification with the small dataset for Quran ontology is the current research problem which appears in Quran ontology development. The existing classification approach used machine learning: Backpropagation Neural Network. However, this method has a drawback; if the training set amount is small, then the classifier accuracy could decline. Unfortunately, Holy Quran has a small corpus. Based on this problem, our study aims to formulate new instances classification framework for small training corpus applied to semantic question answering system. As a result, the instances classification framework consists of several essential components: pre-processing, morphology analysis, semantic analysis, feature extraction, instances classification with Radial Basis Function Networks algorithm, and the transformation module. This algorithm is chosen since it robustness to noisy data and has an excellent achievement to handle small dataset. Furthermore, document processing module on question answering system is used to access instances classification result in Quran ontology

A survey of searching and information extraction on a classical text using ontology-based semantics modeling: a case of Quran

Quran is the religious text of Islam. Followers of Islam believe that it is the verbatim word of Allah (God). In the last few years, the Quran has become a target of interest for researchers in the field of computer science, for exploring the divine knowledge encapsulated in it. Since the last few years ontologies have gained significant importance in computer science research because of its machine understandable and semantic nature. Ontologies play an important role in supporting the notion of the semantic web. Some work has been done on the Quran exploiting the platform of ontologies. This paper presents a survey based on recent works which uses ontologies as a means of representing and encapsulating the knowledge of the Quran. In order to compare the reviewed literature, an authentic framework is used which is applicable to any ontology application. Furthermore, the paper includes a comprehensive comparison table based on the framework which allows the readers to understand the details of all works in a glance. At the end of the paper, the conclusion and future work section highlights the shortcomings of the existing works and give a sense of direction to aspiring researchers in order to contribute to the domain of the Quran