Subjects: Library Science，Information Science >> Information Science submitted time 2023-04-01 Cooperative journals: 《图书情报工作》
Abstract： [Purpose/significance] This paper compared and analyzed the current research status and key functions of representative knowledge organization system (KOS) management tools under the development of semantic web,sorts out the development trends of related research, and provided suggestions for the construction of knowledge organization system in various institutions.[Method/process] Through online survey, 10 representative foreign KOS management tools were selected, and their development status was compared and analyzed from the aspects of structural definition, project maintenance, data government, interoperability, and operating environment. Based on the survey results,we proposed some suggestions for the construction of KOS management tools in China.[Result/conclusion] Relying on the development of technologies such as semantic Web, linked data, semantic integration, and semantic interoperation, the domestic construction of KOS management tools should gradually achieve functional innovation, including flexible design of multiple data models, project management that supports sustainable development, distributed collaborative user management, knowledge driven data updating, semantic-oriented data utilization, KOS as the core of the knowledge organization framework, etc.
Subjects: Library Science，Information Science >> Information Science submitted time 2023-04-01 Cooperative journals: 《图书情报工作》
Abstract： [Purpose/significance] The purpose of this paper is to study the linked data model of publishing the NSTL’s research entity name authority data as linked data. After the name authority data is published as linked data, it can be reused as an open linked data set by other system or organization, and also can be better integrated with other linked data sets to improve data quality. In addition, it also provides a model building reference for other organizations to publish authority data as linked data. [Method/process] First, this paper analyzed and compared the data models used in the linked data publishing projects at home and abroad. It showed that the data models in the linked data publishing projects were mainly divided into two categories. Then, combined with the characteristics of NSTL name authority data, two forms of linked data models were designed. It compared the two models from the expression level of the NSTL’s data and the complexity of the models. The better one was selected. Finally, it used D2RQ as tool to publish the sample data as linked data. [Result/conclusion] The analysis found that the model with Schema.org as the core standard vocabulary has better performance. So it is more suitable as a linked data model for NSTL’s name authority data.
Subjects: Library Science，Information Science >> Information Science submitted time 2023-04-01 Cooperative journals: 《图书情报工作》
Abstract： [Purpose/significance] Aiming at problems of intelligent Q&A based on Q&A pairs such as low accuracy and resolution rate and poor user satisfaction, this paper constructs a knowledge graph (KG) ontology model that supports the realization of dynamic and accurate intelligent Q&A based on the knowledge graph. [Method/process] First, the paper analyzed the current problems and causes of intelligent question answering, and proposed a plan to build a knowledge graph to support intelligent question answering. Second, On the basis of existing ontology model construction methods, the paper proposed a multi-round loop method integrating multi-level data, which used the business data provided by the enterprises, user data and business system dynamic data as the data sources. And the core steps were to build a basic framework, improve the knowledge structure, and align three cycles of the knowledge structure. Finally, this paper took the domain of return and exchange as a case to describe the concrete steps of ontology model construction, from zero, added incrementally, and constructed ontology model of knowledge graph. [Result/conclusion] This paper applies the knowledge graph with the return ontology model as the schema layer in an intelligent Q&A system for testing. The evaluation results show that the accuracy rate increased by 50% and the precision rate increased by 300% after the return and exchange knowledge graph is online. So, the proposed ontology model construction method sorts out the complete and fine-grained domain knowledge structure from scattered domain knowledge, can provide accurate answers to users in intelligent Q&A, and can effectively solve the intelligent Q&A dilemma based on Q&A pairs.
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