Saidah Saad

A framework for Islamic knowledge via ontology representation

Ontology is one of the essential topics in the scope of an important area of current computer science and Semantic Web. Ontologies present well defined, straightforward and standardized form of the repositories (vast and reliable knowledge) where it can be interoperable and machine understandable. There are many possible utilization of ontologies from automatic annotation of web resources to domain representation and reasoning task. Ontology is an effective conceptualism used for the semantic web. However there is none of the research try to construct an ontology from Islamic knowledge which consist of Holy Quran, Hadiths and etc. Therefore as a first stage, we try to identify the framework of Islamic Knowledge in order to develop an ontology, and method for extracting an Islamic concept.

Islamic knowledge ontology creation

Ontology is one of the essential topics in the scope of an important area of current computer science and Semantic Web. Ontologies present well defined, straightforward and standardized form of the repositories (vast and reliable knowledge) where it can be interoperable and machine understandable. There are many possible utilization of ontologies from automatic annotation of web resources to domain representation and reasoning task. Ontology is an effective conceptualism used for the semantic web. However there is none of the research try to construct an ontology from Islamic knowledge which consist of Holy Quran, Hadiths and etc. Therefore as a first stage, in this paper we try to propose a simple methodology in order to extract a concept based on Al-Quran. Finally, we discuss about the experiment that have been conducted.

Keyphrase extraction for Islamic Knowledge ontology

This paper describes ongoing work on the evaluation methods for extraction keyword and keyphrase candidate in order to develop an ontology for Islamic Knowledge. Keyphrases provide semantic metadata that summarize, characterize documents and topic search. The task of automatic keyword and keyphrase extraction and also known as a collocation extraction is to select keywords or keyphrases from within the text of a given document. Automatic keywords or keyphrase extraction makes it feasible to generate keywords or keyphrases for the huge number of documents that do not have manually assigned them. This paper also describes an algorithm for extracting keyphrases from Islamic Knowledge text as a concept and attribute candidate. It identifies candidate keywords and keyphrases using lexico-syntactic method and statistical method.

Pattern extraction for Islamic concept

Ontology is one of the essential topics in the scope of an important area of current computer science and Semantic Web. Ontologies present well defined, straightforward and standardized form of the repositories (vast and reliable knowledge) where it can be interoperable and machine understandable. There are many possible utilization of ontologies from automatic annotation of web resources to domain representation and reasoning task. Ontology is an effective conceptualism used for the semantic web. However there is none of the research try to construct an ontology from Islamic knowledge which consist of Holy Quran, Hadiths and etc. Therefore as a first stage, in this paper we try to propose a simple methodology in order to extract a concept based on Al-Quran. Finally, we discuss about the experiment that has been conducted.

Rules and Natural Language Pattern in Extracting Quranic Knowledge

The extraction of Quranic knowledge is a challenging task since the Quran is different from human literature. The unique arrangement of its texts has made the task of directly accessing its meaning, which is rich in its linguistics and multi-layered meanings, difficult if done without the use of other resources such as the Hadith. Hence, this paper describes the extraction of the first layer and the use of natural language pattern in extracting the knowledge of Quranic English translation texts using natural language processing techniques. Evaluation is performed using the true positive, false positive and false negative metrics and encouraging results have been obtained.

An early stage of knowledge acquisition based on Quranic text

In this paper, we present our early stage on developing Ontology for Quranic translation English Text using ontology learning techniques. For this stage, we are focusing on the Solat subject. We explain the requirement to create the ontology based on understanding of the Quranic translation text. At the same time we discuss the creation of gold standard in order to evaluate the finding pattern based on ontology learning techniques.

Towards Building Semantic Rich Model for Web Documents Using Domain Ontology

Accessing and extracting semantic meanings from web documents is crucial for the realization of Semantic Web. While the web offers the flexibility of making information easily available, it is considerably hard to find a fruitful way to describe, classify and present this information with rich semantic content. Therefore, the semantic information content of web documents need to be specified in order to make the tangled information more accessible to search engines and other applications. In this paper we propose an approach meant to assist in constructing semantic document models using natural language analysis technique and a domain specific ontology.

Review of personalized learning approaches and methods in e-learning environment

Personalized E-learning topic has attracted the interest of many research studies in recent years. This paper provide a survey of the previous research works done regarding personalized environment. Two main concepts will be discusses including approaches that have been used, learning styles identification techniques and methods involved as well as its learning styles. The approaches consist of collaborative and automatic while methods for automatic learning style detection involved data-drive and literature-based. Finally, from all the previous study that have been discussed, the author aims to introduce a personalized e-learning system based on the concepts of learning styles and particularly the Felder and Silverman Learning Style Model (FSLSM).

Term extraction and hierarchy induction method based on islamic dictionary

A machine readable dictionary (MRD) is an electronic dictionary that enables query processing. One of the common processing tasks that has been widely applied is Concept Hierarchy Induction which aims at identifying concepts with its corresponding taxonomies. The existing concept hierarchy approaches for Islamic domain are using limited linguistic patterns. This study aims to propose an unsupervised concept hierarchy induction for the Islamic domain by extending the patterns and rules. In fact, Term Frequency-Inverse Document Frequency (TF-IDF) was carried out in order to identify the most frequently used concepts. Furthermore, two syntactical features were used including POS tagging and chunk parser in order to identify the tagging for each word (e.g. verb, noun, adjective, etc.) and extracting Noun Phrases (NP). Hence, the proposed extension patterns aim at utilize lexico-syntactic patterns to induce the concept hierarchy. That demonstrates the usefulness of extending patterns for the Islamic domain.