物流本体数据库的应用研究

文章以利用Protégé和SQL Server 2000相结合,构建物流本体数据库为例,充分利用DBMS特点,弥补检索与匹配RDF或OWL本体数据效率低的不足,给出创建与应用本体数据库的模式,为物流领域的不同企业、不同部门之间管理语义异构、结构异构的数据提供了一种全新的方式,并体验物流本体技术在物流领域的应用价值。

基于同义词表的异构数据库-本体映射

本体是信息在语义层和知识层的描述。将现有的其它数据形式转换为本体表示将有利于实现数据共享和语义推理。目前计算机系统中的数据大多以关系数据库形式存在,因此基于关系数据库构建本体的研究具有重要意义。本文首先分析了单一数据库-本体映射问题,扩充了Ghawi规则以覆盖更多类型的数据关系,其次针对同质异构数据库-本体映射问题,进一步扩充Ghawi规则,给出了基于同义词表的异构数据库-本体映射规则集,实现了异构数据库-本体映射。

基于关系数据库的油田领域数据质量本体构建

为实现对油田数据质量全方位、规范的描述,以石油领域的相关专业的数据为研究背景,借助于现代先进的本体理论,基于已有的油田数据质量关系数据库资源,抽取出相关概念模型,再将概念模型转换成OWL本体,尝试构建出集数据质量管控于一体的规范的石油领域数据质量本体模型。

中国健康信息数据集的一种本体处理架构

针对中国健康信息数据集规范不支持语义集成、自动处理和推理,在DescriptionLogics数学基础上,提出一种基于本体数据库的知识基(KBS)处理架构。该架构将健康信息数字化建设纳入知识工程轨道,提供一个庞大、规范、可靠、安全、可维护的KBS。以婚前体格检查数据集为案例说明,结果证明该架构可实现知识的自动处理和推理。

从开放设计到元设计(metadesign)--3D打印数据库本体的冲击

3D打印技术日益成熟并开始为诸多领域所应用,已经并将持续对科学技术和人类生活各个领域产生革命性影响。而3D打印与其他科学技术特别是生物技术一样,毁誉参半,对其是否应该广泛应用争论不下。文章将从3D打印对设计界的影响,特别是对于计算机本体数据库的应用角度分析、阐释该技术的优势及其广泛应用的不可回避性,提醒要重视其负面效应。

军事物流业务流引擎ODB建模方法初探

为提高军事物流业务流引擎应用本体(Military Logistics Business Flow Engine Special Ontology,MLBFEO)的维护与实践应用的效率与可靠性。文章对Protégé、Jena API等持久化OWL文件到本体数据库(Ontology Database,ODB)的表结构、数据元素关系分析基础上,提出了基于RDBMS与RDF"三元组"核心思想,设计了军事物流业务流ODB的结构。文章构建的军事物流业务流ODB为军事物流业务流引擎(MLBFE)的维护和基于MLBFE的业务管理信息系统[1](BMIS)开发夯实了数据结构根基。

Domain semantic mapping of database metasearch engine

In order to implement semantic mapping of database metasearch engines, a system is proposed, which uses ontology as the organization form of information and records the new words not appearing in the ontology. When the new word＇ s frequency of use exceeds the threshold, it is added into the ontology. Ontology expansion is implemented in this way. The search process supports ＂and＂ and ＂or＂ Boolean operations accordingly. In order to improve the mapping speed of the system, a memory module is added which can memorize the recent query information of users and automatically learn the user＇ s query interest during the mapping which can dynamically decide the search order of instances tables. Experiments prove that these measures can obviously reduce the average mapping time.

Construction and application of knowledge graph of Treatise on Febrile Diseases

Objective To establish the knowledge graph of“disease-syndrome-symptom-method-formula”in Treatise on Febrile Diseases(Shang Han Lun,《伤寒论》)for reducing the fuzziness and uncertainty of data,and for laying a foundation for later knowledge reasoning and its application.Methods Under the guidance of experts in the classical formula of traditional Chinese medicine(TCM),the method of“top-down as the main,bottom-up as the auxiliary”was adopted to carry out knowledge extraction,knowledge fusion,and knowledge storage from the five aspects of the disease,syndrome,symptom,method,and formula for the original text of Treatise on Febrile Diseases,and so the knowledge graph of Treatise on Febrile Diseases was constructed.On this basis,the knowledge structure query and the knowledge relevance query were realized in a visual manner.Results The knowledge graph of“disease-syndrome-symptom-method-formula”in the Treatise on Febrile Diseases was constructed,containing 6469 entities and 10911 relational triples,on which the query of entities and their relationships can be carried out and the query result can be visualized.Conclusion The knowledge graph of Treatise on Febrile Diseases systematically realizes its digitization of the knowledge system,and improves the completeness and accuracy of the knowledge representation,and the connection between“disease-syndrome-symptom-treatment-formula”,which is conducive to the sharing and reuse of knowledge can be obtained in a clear and efficient way.

A Parsing Graph-based Algorithm for Ontology Mapping

Ontology mapping is a critical problem for integrating the heterogeneous information sources. It can identify the elements corresponding to each other. At present, there are many ontology mapping algorithms, but most of them are based on database schema. After analyzing the similarity and difference of ontology and schema, we propose a parsing graph-based algorithm for ontology mapping. The ontology parsing graph （OP-graph） extends the general concept of graph, encodes logic relationship, and semantic information which the ontology contains into vertices and edges of the graph. Thus, the problem of ontology mapping is translated into a problem of finding the optimal match between the two OP-graphs. With the definition of a universal measure for comparing the entities of two ontoiogies, we calculate the whole similarity between the two OP-graphs iteratively, until the optimal match is found. The results of experiments show that our algorithm is promising.

Dacura平台——历史研究的数据收集和知识提取新途径

随着计算机科技的进步,我们可以解决历史学家在收集和评估基于互联网的海量数据时遭遇到的各类问题。作为范例,本文介绍Dacura数据维护平台。它被用来协助历史研究者从互联网或者其他数据源收集、分析、维护高质量数据。Dacura使用语义知识图谱技术将数据表示为复杂的、相互关联的知识,在不需要查询表的情况下,允许快速搜索和检索特定数据。Dacura使各种工具的生产自动化,以帮助非专业人士逐步构建高质量的知识库,并从大量数据源里将数据整合进它的知识综合维护模型中。Dacura平台所具有的这些特性,为用户快捷地收集和自动分析来自互联网的资源提供了新的途径。本文将为读者提供一个Dacura平台实际操作的范例:这一平台如何应用于填充和管理Seshat数据库。