An Adaptable Ontology for Easy and Efficient University Data Management in Niger Delta University (Published)
The structure, variety and quantity of some current web content is limited in efficient exploration due to difficulty in searching and locating a specific content. A case is the Niger Delta University where there is no unified online structure holding relevant university data. This is because there is no common data model to manage the data for which such query can easily be interpreted semantically. Therefore, this paper presents the application of semantic web technology for the unification of university data management. This research prepares the ground for the advent of software agents and other applications that require structured data for its computational processes. The ontology development follows an iterative path of the Object-Oriented System Analysis and Design (OOSAD) methodology. SPARQL was used as the query language for testing the ontology. The result is a semantically structured data that is deployable which can be expended and adapted in other institutions.
Keywords: Database, Ontology, sparql
Towards Integration of Ontologies in Healthcare (Published)
Digital health is facing many challenges. Nowadays the use of ontologies in health care has increased and is covering wide range domains in healthcare. Using ontologies may improve the semantic interoperability and also offer the possibility to gain knowledge from them. It is significantly important not only to implement ontologies in healthcare but to integrate them in order to benefit from different ontologies. In this paper, we provide a comprehensive overview of the importance, advantages and challenges in integrating ontologies through a semantic mapping scenario between two ontologies. Integration of ontologies may support the decision-making process of healthcare providers by deriving relationships between different sets of conditions, findings, signs or symptoms.
Keywords: Healthcare, Integration, Mapping, Ontology
A HYBRID AND PERSONALIZED ONTOLOGY RANKING MODEL USING U-MEANS CLUSTERING AND HIT COUNT (Published)
Semantic Web is an extension of current Web which offers to add structure to the present Web. Ontologies play an important role in Semantic Web development and retrieval of relevant ontology. Ontology is being represented as a set of concepts and their inter-relationships relevant to some knowledge domain. As the number of Ontology repositories are more on Semantic Web, the problem of retrieving relevant ontologies of the scope arises. Even though there are Semantic Web search engines available, a major problem is that the huge number of results returned and which gives overhead to the searcher to find their need by themselves after going through the long list. This makes time consumption in search and creates dissatisfaction. One solution for this problem is that of maintaining the history of already analyzed, highly relevant and quality results in a log, which can used quickly to respond to the users of the similar type. This places highly relevant results analyzed and stored on the top list when results are presented to the searcher. Personalization and ranking takes care of these approaches. Another solution is the integration of clustering approach which helps in retrieving results from the history or log faster. This paper proposes a hybrid approach that creates the log and retrieves from log when the query is known and there are sufficient entries in the log. This approach imparts convenience to users and reduces the time complexity in finding their relevant needs.
Keywords: Clustering., Ontology, Ontology Ranking, Personalization, Semantic Search, Semantic Web
Development of HealthCare System for Smart Hospital Based on UML and XML (Published)
The convergence of information technology systems in health care system building is causing us to look at more effective integration of technologies. Facing increased competition, tighter spaces, staff retention and reduced reimbursement, today’s traditional hospitals are looking at strategic ways to use technology to manage their systems called smart hospital. The concept of the smart hospital is a useful system for any hospital; about adding intelligence to the traditional hospital system by covering all resources and locations with patient information. Patient’s information is an important component of the patient privacy in any health care system that is based on the overall quality of each patient in the health care system. The main commitment for any health care system is to improve the quality of the patient and privacy of patient’s information. Today, there is a need of such computer environment where treatment to patients can be given on the basis of his/her previous medical history at the time of emergency at any time, on any place and anywhere. Pervasive and ubiquitous environment and UML (unified modeling language) can bring the boon in this field. For this it’s needed to develop the ubiquitous health care computing environment using the UML with traditional hospital environment. This paper is based on the ubiquitous and pervasive computing environment based on UML and XML(The Extensible Markup Language) technology, in which these problems has been tried to improve traditional hospital system into smart hospital in the near future. The key solution of the smart hospital is online identification of all patients, doctors, nurses, staff, medical equipments, medications, blood bags, surgical tools, blankets, sheets, hospital rooms, etc. In this paper efforts is channeled into improving the knowledge-base ontological description for smart hospital system by using UML and XML technology, Our knowledge is represented in XML format from UML modeling(class diagram). Our smart hospital provides access to its system by using a smart card. Finally, the former try to improve health care delivery through development and management of acute care hospital designed; both physically and operationally, for more efficiency and increased patients safety
Keywords: Health Care System, Ontology, Smart Hospital (SH), UML, XML