Ph.D. student, badji mokhtar university
In spite of the efforts made in the Arabic language on the syntactic and semantic level, it remains very restricted, even those on the Arabic Sacred Book are few and very limited, due to its difficulties and peculiarities. In this paper we tried to shed the light on some of the recent works that have been conducted to present a semantic representation and manipulation of the Islamic texts to define the problems, limitations and the possible future works that need our intention to improve the semantic support in the Arabic religious texts. Furthermore, we intent to briefly present our project that aims to help us reading, understanding, and interpreting the Islamic legislative sources. The goal of this project is divided into two main tasks which are the creation of an ontology representing the Islamic knowledge and the development of a system which can analyze this knowledge. The ultimate goal is to assist the muftis and facilitate their job.
Abstract: The dramatic increase in the use of knowledge discovery applications requires end users to write complex database search requests to retrieve information. Such users are not only expected to grasp the structural complexity of complex databases but also the semantic relationships between data stored in databases. In order to overcome such difficulties, researchers have been focusing on knowledge representation and interactive query generation through ontologies, with particular emphasis on improving the interface between data and search requests in order to bring the result sets closer to users research requirements. This paper discusses ontology-based information retrieval approaches and techniques by taking into consideration the aspects of ontology modelling, processing and the translation of ontological knowledge into database search requests. It also extensively compares the existing ontology-to-database transformation and mapping approaches in terms of loss of data and semantics, structural mapping and domain knowledge applicability. The research outcomes, recommendations and future challenges presented in this paper can bridge the gap between ontology and relational models to generate precise search requests using ontologies. Moreover, the comparison presented between various ontology-based information retrieval, database-to-ontology transformations and ontology-to-database mappings approaches provides a reference for enhancing the searching capabilities of massively loaded information management systems.
Pub.: 01 Aug '17, Pinned: 13 Nov '17
Abstract: An application of Narrative Knowledge Representation Language (NKRL) techniques on (declassified) ‘terrorism in Southern Philippines’ documents has been carried out in the context of the IST Parmenides project. This paper describes some aspects of this work: it is our belief, in fact, that the Knowledge Representation techniques and the Intelligent Information Retrieval tools used in this experiment can be of some interest also in an ‘Ontological Modelling of Legal Events and Legal Reasoning’ context.
Pub.: 13 Feb '07, Pinned: 13 Nov '17
Abstract: To summarize the best papers in the field of Knowledge Representation and Management (KRM).A comprehensive review of medical informatics literature was performed to select some of the most interesting papers of KRM published in 2014.Four articles were selected, two focused on annotation and information retrieval using an ontology. The two others focused mainly on ontologies, one dealing with the usage of a temporal ontology in order to analyze the content of narrative document, one describing a methodology for building multilingual ontologies.Semantic models began to show their efficiency, coupled with annotation tools.
Pub.: 22 Aug '15, Pinned: 13 Nov '17
Abstract: Fuzzy knowledge is prevalent in real life, and ontology is the main way of knowledge representation in semantic web. In this paper, two main kinds of common fuzzy knowledge are sorted out, and there is a great significance for ontology representation of common fuzzy knowledge in semantic web. In addition, searching knowledge in ontology is the most common operation of semantic web, but heterogeneous ontologies seriously affect accuracy of information retrieval, and ontology mapping is the key to solve the problem. Therefore, in this paper, firstly an ontology representation method of common fuzzy knowledge is presented. Common fuzzy knowledge is polytypic and includes most commonly used fuzzy knowledge in reality. So fuzzy sets and Cloud Model are used to reflect and represent these 2 types of common fuzzy knowledge in ontology. Then, based on the ontology representation method of common fuzzy knowledge mentioned above, a corresponding algorithm of ontology mapping is presented, which is based on similarity calculation of concepts and Support Vector Machine. The proposed methods extend the scope of ontology application and are significant for information retrieval of fuzzy knowledge in the semantic web. The experiments show that the proposed methods are practicable and effective.
Pub.: 11 Jun '16, Pinned: 13 Nov '17
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