Research and Implementation of Mine Risk Area Semantic Retrieval System Based on Ontology

In this paper, the authors first analyze the research and development of semantic retrieval technology based on ontology, and introduce the key theoretical knowledge of ontology and semantic web, including the definition, description language, classification and semantic web. Secondly, this thesis makes a deep research on the ontology based semantic retrieval including semantic annotation, Chinese word segmentation, ontology storage, semantic association algorithm and so on. At the same time, it analyzes and introduces the construction principle, methods and tools involved in ontology. Finally, this paper designs and implements a complete ontology based semantic retrieval system based on the ontology of coal mine risk domain ontology, and verifies the feasibility of the system and the theory, and provides the basis for the development and popularization of the ontology based semantic retrieval technology.

Atmospheric Lidar Data Storage Model Based on Ontology

Ontology is an effective method to solve the problem of heterogeneous data in lidar measurements. Due to complexity and diversity of data structure, traditional method of ontology storage cannot be directly applied to lidar data. In this work, we proposed a novel ontology storage model based on the object-oriented data model, in which the mapping mechanism was established from ontology of lidar data to the object-oriented data model. A new storage model of lidar data is then obtained by a combination of the characteristics of lidar data and the syntax of OWL DL. Compared to the traditional method of ontology storage, we believe that the new storage model can better serve the sharing of lidar data.

Ontology Storage Models and Tools: An Authentic Survey

Ontology is a formal, explicit specification of a shared conceptualization. Ontology provides domain vocabulary, domain knowledge, common understanding, shareability, information interoperability, reusability, concept hierarchy, and relationships that support semantic information retrieval. Ontology improves performance of the system by addressing interoperability issues due to semantic and syntactic heterogeneity. Vast numbers of application domain experts are using ontologies in diverse applications. Use of effective and efficient ontology storage system results improved performance in applications and enables semantic information retrieval. Many prominent researchers and software agencies have proposed and developed several ontology storage methods and tools with various features. The choice of a specific storage model/tool always depend on the specific purpose of the application and the nature of features that are available in the storage model/tool to be utilized in the specific applications. The familiarity of various ontology storage models and tools with the respective features helps user to choose an appropriate storage structure aiming at high-performance applications. The current research work is a comprehensively authentic study carryout out on various ontology storage models and tools with their respective features, which are very essential for optimum performance.

Research and Implementation of Mine Risk Area Semantic Retrieval System based on Ontology

In this paper, the authors first analyze the research and development of semantic retrieval technology based on ontology, and introduce the key theoretical knowledge of ontology and semantic web, including the definition, description language, classification and semantic web. Secondly, this thesis makes a deep research on the ontology based semantic retrieval including semantic annotation, Chinese word segmentation, ontology storage, semantic association algorithm and so on. At the same time, it analyzes and introduces the construction principle, methods and tools involved in ontology. Finally, this paper designs and implements a complete ontology based semantic retrieval system based on the ontology of coal mine risk domain ontology, and verifies the feasibility of the system and the theory, and provides the basis for the development and popularization of the ontology based semantic retrieval technology.

Ontology Integration Framework Based on XMDR+

Ontology integration carries significant importance in terms of reuse of knowledge and interoperability. In this paper, a framework for ontology integration based on extended metadata registry plus (XMDR+) is focused, that is, we try to developer a methods for ontology integration to provide high quality Semantic Web services. To sum up, the ontology integration framework proposed herein not only produces global ontologies; but also defines such methods, and, thereby, performs better in extending and integrating ontologies. The framework will rely on a model independent of ontology storage structures, but will be capable of representing semantic relationships between different ontology systems.