Research On Construction Of Water Environment Domain Ontology From Web Data

Water environment is closely related to our daily life, the present situation of water pollution in China is very serious, comprehensive management of water environment is imminent. Using information technology innovation of the water environment management model to promote water conservancy information technology, is currently the focus of water science and technology innovation. But between the mass of information resources exist the problems of grammar, semantics and structure of heterogeneous data, resulting in data discovery, data assimilation, resource sharing and application is very complicated and inefficient, greatly affected the efficiency and reliability of basin water resources management and environmental control modeling and decision.To the problem of heterogeneous information and the knowledge representation difference, this paper introduces ontology as a kind of information standardization.Ontology can solve the problem such as knowledge representation, knowledge organization and knowledge sharing. Ontology as a new method to describe the ontology concept hierarchy and semantic model, is widely used in the field of information retrieval and information extraction, semantic web, knowledge engineering,artificial intelligence.This paper briefly introduces the basic theoretical knowledge of ontology, such as the definition, classification, architecture, description language, and studies ontology learning,which is the key technology of building ontology. Ontology learning mainly includes the concept extraction and relation extraction. This paper proposes a concept extration method based on genetic algorithm and a relation extraction method based association rules, and its are applied in the field of water environment ontology learning.Designed and implemented a system of water environment domain ontologyconstruction. According to the process of ontology construction, the system is divided into five subsystems: data acquisition subsystem, data preprocessing subsystem, concept extraction subsystem, relation extraction subsystem, ontology visualization subsystem.In this system, the collected data source after processing to form the candidate set of concepts, then extracting domain concepts and their relations from the candidate set, and eventually editing its to the water environment domain ontology, and visual display.