Research And Application Of Classification And Search Tools For Scientific Literature Information In Water Resources And Hydropower Field

A lot of subjects of Water Resources and Hydropower field have cross overlapping characteristics, most of the documents are non-books those are continuously produced every year,The level of development of information technology needs to be improved. Document classification system is built in this paper, Ontology is applied to document retrieval technology, ontology model of Water Resources and Hydropower field is designed, and ontology instance library is built. Based on ontolgy instance library, retrieval core algorithm is resarched, and document retrieval system is designed and developed. Comparison test of retrieval method of ordinary keyword and semantic expansion search is analyzed at last, the major work is summarized as follows:Classification systems of Water Resources and Hydropower technology literature are not clear enough, Based on resarch on existing classification systems, a new classification system for scientific literature retrieval of information is constructed, Considering the characteristics of water conservancy and hydropower field.Key technologies of literature information retrieval system are studied, including representation and description of ontology model,domain concepts acquisition, and ontology library retrieval technology, the jobs supply the theoretical foundation for research and development of retrieval system.In this paper, the jobs of needs analysis, architecture framework and function modules for literature retrieval system are completed, algorithmic process and building of ontology library are described in detail.According to semantic retrieval key technologies and domain ontology model of Water Resources and Hydropower field, prototype system has been developed, discussing key technologies, key technologies, development tools, storage solutions, reasoning and semantic retrieval process.The jobs of comparison test of retrieval method of ordinary keyword and semantic expansion search is completed, the "seven-step" construction methodology and classification system are verified at last.