领域本体驱动下企业联机分析处理系统应用研究

doi:10.11772/j.issn.1001-9081.2016.01.0254

计算机应用 ›› 2016, Vol. 36 ›› Issue (1): 254-259.DOI: 10.11772/j.issn.1001-9081.2016.01.0254

领域本体驱动下企业联机分析处理系统应用研究

刘馨蕊¹, 任凤玉², 雷国平¹

1. 东北大学土地管理所, 沈阳 110819;
2. 东北大学采矿所, 沈阳 110819

收稿日期:2015-07-10 修回日期:2015-09-18 出版日期:2016-01-10 发布日期:2016-01-09
通讯作者: 刘馨蕊(1984-),女,辽宁本溪人,讲师,博士,主要研究方向:数字矿山、数据集成、知识管理、3S技术与地学系统
作者简介:任凤玉(1956-),男,内蒙古敖汉旗人,教授,博士,主要研究方向:采矿工艺、采矿方法;雷国平(1963-),男,黑龙江青冈人,教授,博士,主要研究方向:土地经济、土地利用规划、国土资源管理。
基金资助:
国家自然科学基金资助项目(71501036);中央高校基本科研业务费专项(N141403001)。

Research of domain ontology driven enterprise on-line analytical processing systems

LIU Xinrui¹, REN Fengyu², LEI Guoping¹

1. Institute of Land Management, Northeastern University, Shenyang Liaoning 110819, China;
2. Institute of Mining Engineering, Northeastern University, Shenyang Liaoning 110819, China

Received:2015-07-10 Revised:2015-09-18 Online:2016-01-10 Published:2016-01-09
Supported by:
This work is partially supported by the National Natural Science Foundation of China (71501036) and the Fundamental Research Funds for the Central Universities (N141403001).

摘要/Abstract

摘要： 传统联机分析处理(OLAP)系统存在着形式化业务知识参与不足的状况,对深度推理分析造成了制约和局限。为了克服上述缺点,提出一种领域本体驱动的OLAP系统构建方法。首先,通过分析现有本体构建方法的局限性,依托实体类多特征加权相似度判断算法,提出先全局设计后局部抽取的半自动本体构建模式,实现矿山生产领域知识形式化;接着在此基础上,以矿山生产能力关键指标为度量,完成负载业务概念多维本体(MDO)建模;最后,在实际矿山决策系统项目建设中,进行了方法检验。实验结果表明,该方法充分发挥领域本体形式化表达与推理优势,有效整合多源异构信息和明晰多维分析过程,实现内隐知识与关联规则深度挖掘;同时借助高频通用概念视图定义,避免重复维度建模,改进了传统OLAP效能。

关键词: 联机分析处理, 领域本体, 语义知识, 多维本体, 矿山生产

Abstract: At present the insufficient formal business knowledge participation in the process of On-Line Analytical Processing (OLAP) results in restriction and limitation to in-depth analysis. To overcome the limitations, a new approach for building an OLAP system was proposed based on domain ontology. Firstly, by analyzing the limitations of the existing ontology construction methods and using the similarity evaluation algorithm based on multiple features and weighted pattern of entity classes, a semi-automatic domain ontology construction method in which global top-level domain ontology was designed by experts after local ontologies were generated from databases was put forward to implement formalized description of mine-production domain knowledge. And then the key indicators of mine-production capacity were chosen as measurements and Multi-Dimensional Ontology (MDO) with business semantic concepts was built. Finally, the method was tested by a practical project of metal mine decision making system. The experimental results show that the proposed method can dynamically integrate heterogeneous information resource of mine production process and facilitate the unambiguous interpretation of query results, and discover association rules and implicit knowledge through the advantages of formalization expression and reasoning of domain ontology. Meanwhile, by high frequency and general concept views, it avoids query duplication and improves the performance of traditional OLAP systems.

Key words: On-Line Analytical Processing (OLAP), domain ontology, semantic knowledge, Multi-Dimensional Ontology (MDO), mine production

中图分类号:

TP18
CP931.9

刘馨蕊, 任凤玉, 雷国平. 领域本体驱动下企业联机分析处理系统应用研究[J]. 计算机应用, 2016, 36(1): 254-259.

LIU Xinrui, REN Fengyu, LEI Guoping. Research of domain ontology driven enterprise on-line analytical processing systems[J]. Journal of Computer Applications, 2016, 36(1): 254-259.

参考文献

[1] RIZZI S, ABELLÓ A, LECHTENBÖRGER J, et al. Research in data warehouse modeling and design: dead or alive? [C]// Proceedings of the International Workshop on Data Warehousing and OLAP. New York: ACM, 2006: 3-10.
[2] KIMBALL R, ROSS M. The data warehouse toolkit: the complete guide to dimensional modeling [M]. New York: Wiley, 2002: 13-15.
[3] INMON B. Building the data warehouse [M]. New York: Wiley, 2005: 29-69.
[4] VAISMAN A, ZIMANYI E. Data warehouses: next challenge [C]// eBISS 2011: Proceedings of the 2011 International Conference on e-Business and Information System Security. Berlin: Springer, 2011: 1-25.
[5] 石勇,张玲玲,陈懿冰.智能知识管理发展研究[C]// 2012—2013年管理科学与工程学科发展报告.北京:中国科学技术出版社,2014:61-81.(SHI Y, ZHANG L L, CHEN Y B. Research on the development of intelligent knowledge management [C]// Management Science and Engineering Discipline Development Report 2012—2013. Beijing: China Science and Technology Press, 2014: 61-81.)
[6] 古志文,陈春,吴新年.支撑企业技术创新的知识服务模式研究 [J].科技进步与对策,2014, 31(7):131-135.(GU Z W, CHEN C, WU X N. Study on knowledge service pattern for supporting technology innovation of enterprise [J]. Science & technology progress and policy, 2014, 31(7): 131-135.)
[7] GUARINO N. Semantic matching: formal ontological distinctions for information organization, extraction, and integration [C]// SCIE'97: International Summer School on Information Extraction: a Multidisciplinary Approach to an Emerging Information Technology. Berlin: Springer, 1997: 139-170.
[8] 吴立新,徐磊,陈学习,等.基于主体人与地学本体的人-地-GIS关系讨论[J].地理与地理信息科学,2006,22(l):1-6.(WU L X, XU L, CHEN X X, et al. Human-earth-GIS relations discussion based on subject-human and geo-ontology [J]. Geography and geo-information science, 2006, 22(l): 1-6.)
[9] 吴立新,徐磊,车德福.地层本体及其在大区域钻孔数据集成中的应用[J].武汉大学学报(信息科学版),2008,33(2):144-145.(WU L X, XU L, CHE D F. Stratum-ontology and its application in borehole data integration [J]. Geomatics and information science of Wuhan university, 2008,33(2):144-145.)
[10] 戴露,李成,彭明.基于地理本体的矿山地测数据组织方法研究[J].金属矿山,2010(5):107.(DAI L, LI C, PENG M. Study on geospatial data organization of mine based on geographic ontology [J]. Metal mine, 2010(5): 107.)
[11] 肖锁云.基于本体的金属矿山采矿区供电管理地理信息系统研究[D].南京:南京师范大学,2012:15-34.(XIAO S Y. Research on mining area power supply management geographic information system of metal mine based on ontology [D]. Nanjing: Nanjing Normal University, 2012: 15-34.)
[12] PRAT N, AKAOKA J, COMYN-WATTIAU I. Transforming multidimensional models into OWL-DL ontologies [C]// Proceedings of the 2012 IEEE Sixth International Conference on Research Challenges in Information Science. Piscataway, NJ: IEEE, 2012: 1-12.
[13] NEUBÖCK T, NEUMAYR B, SCHREFL M, et al. Ontology-driven business intelligence for comparative data analysis [C]// eBISS 2013: Business Intelligence-Third European Summer School. Berlin: Springer, 2014: 77-120.
[14] CIMIANO P, VOLKER J. Text2onto a framework for ontology learning and data-driven change discovery [C]// NLDB'05: Proceedings of the 10th International Conference on Natural Language Processing and Information Systems. Berlin: Springer, 2005: 227-238.
[15] 杜振兴.面向爆破行业的领域本体自动提取技术研究[D].广州:华南理工大学,2011:18-51.(DU Z X. Research of domain ontology automatically extracting technology orienting to blasting industry [D]. Guangzhou: South China University of Technology, 2011: 18-51.)
[16] 冯波,郝文宁,宋杰,等.基于关系数据库的军事训练本体自动构建模型[J].指挥信息系统与技术,2013,4(5):18-23.(FENG B, HAO W N, SONG J, et al. Auto-constructed model for military training ontology based on relational database [J]. Command information system and technology, 2013, 4(5): 18-23.)
[17] NEUMAYR B, SCHVTZ C, SCHREFL M. Semantic enrichment of OLAP cubes: multi-dimensional ontologies and their representation in SQL and OWL [C]// ODBASE'13: Proceedings of the 12th International Conference on Ontologies, Databases, and Applications of Semantics. Berlin: Springer, 2013: 624-641.
[18] 任柏青.基于关系数据库的领域本体构建方法的研究与实践[D].北京:北京邮电大学,2009:34-72.(REN B C. Research and practice on a mechanism of generating ontology based on relational database [D]. Beijing: Beijing University of Posts and Telecommunications, 2009: 34-72.)
[19] ZHAI B R, ZHONG Z N. An approach of extracting from relational database to OWL ontologies [J]. Computer & information technology, 2011(10):1-4.(翟保荣,钟志农.一种基于关系数据库提取OWL本体的方法[J].计算机与信息技术,2011(10):1-4.)
[20] KAVOURAS M, KOKLA M. Theories of geographic concepts [M]. Boca Raton, USA: CRC Press, 2007: 222-248.
[21] 罗军,陈波.关系数据库存储OWL本体方法的研究[J].计算机工程,2010,36(21):71-75.(LUO J, CHEN B. Research on method about relational database storing OWL ontology [J]. Computer engineering, 2010, 36(21): 71-75.)
[22] 刘馨蕊.矿山生产数据集成系统构建与应用研究[D].沈阳:东北大学,2013:145-175.(LIU X R. Research on construction and application of mine production data integration system [D]. Shenyang: Northeastern University, 2013: 145-175.)

领域本体驱动下企业联机分析处理系统应用研究

Research of domain ontology driven enterprise on-line analytical processing systems

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

[1]	刘专, 韩瑞琛, 张延松, 陈跃国, 张宇. 面向多核CPU和GPU平台的数据库星形连接优化[J]. 计算机应用, 2021, 41(3): 611-617.
[2]	马冬雪, 宋设, 谢振平, 刘渊. 领域本体驱动的招投标网页解析方法[J]. 计算机应用, 2020, 40(6): 1574-1579.
[3]	赵一, 段兴, 谢仕义, 梁春林. 面向特定目标自识别的交通图像语义检索方法[J]. 计算机应用, 2020, 40(2): 553-560.
[4]	马建刚, 张鹏, 马应龙. 基于知识块摘要和词转移距离的高效司法文档分类[J]. 计算机应用, 2019, 39(5): 1293-1298.
[5]	萨初日拉, 周国亮, 时磊, 王刘旺, 石鑫, 朱永利. Spark环境下并行立方体计算方法[J]. 计算机应用, 2016, 36(2): 348-352.
[6]	周国亮, 萨初日拉, 朱永利. Spark环境下基于多维布隆过滤器的星型连接算法[J]. 计算机应用, 2016, 36(2): 353-357.
[7]	张沪寅张铭洋李鑫. 基于领域本体的电子学习资源库模型[J]. 计算机应用, 2012, 32(01): 191-195.
[8]	李华昱欧阳纯萍徐九韵. 基于领域本体和关系模型的XML语义集成方法研究[J]. 计算机应用, 2011, 31(12): 3258-3263.
[9]	陈琨张蕾. 基于知识图的领域本体构建方法[J]. 计算机应用, 2011, 31(06): 1664-1666.
[10]	何昭青周攀杨科华. 基于社区划分的联机分析处理查询优化方案[J]. 计算机应用, 2010, 30(12): 3371-3373.
[11]	于静吴国全卢燚. 基于领域本体的政务信息检索系统[J]. 计算机应用, 2010, 30(06): 1664-1667.
[12]	刘双印. 电子商务智能推荐系统中基于领域本体的案例检索算法[J]. 计算机应用, 2010, 30(05): 1304-1308.
[13]	汪清明. 基于领域本体的Web服务动态组合模型[J]. 计算机应用, 2009, 29(07): 1957-1959.
[14]	聂立钟珞. 主动服务中程序挖掘系统框架的设计与实现[J]. 计算机应用, 2009, 29(07): 1767-1770.
[15]	杜金洋杨春. 基于关键词语义扩展的检索策略[J]. 计算机应用, 2009, 29(06): 1575-1577.