基于多维多值概念格的矿山生产地学本体构建研究
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摘要
矿山生产地学本体能够形式化描述领域概念,是实现多源异构信息集成与知识共享的关键技术之一。本文从多维地学数据源兼有同一性和特异性的视角入手,扩充多维多值概念格理论,构建兼顾全局和区域特性的地学境本协同语义模型与形式化描述,依托二者映射转换关系,提出强情境敏感性的多维地学结构化数据本体自动学习算法;并以金属矿山实际项目为例,结合矿山生产概念体系架构,构建矿山生产领域本体实例,验证方法有效性。该方法注重地学领多维特性,较客观地展示多维地学对象之间关联关系,且较顾忌局部区域时空等数据环境差异,有效提高矿山生产本体的构建效率与准确性,对其他地学领域本体构建提供借鉴。
Mine production includes geological survey and excavation, and is the fundamental activity for mine enterprise. Data related to mine production are typically geospatial, showing high space, temporal complexity and multi-scale. Geo-ontology can be applied to clearly describe and formalize geo-concepts, integrate heterogeneous geo-information and share geo-knowledge. However, several problems currently exist in the constructing process of using this new technique: efficiency resulting from extensive human involvement in the building process of geo-ontology, and the low accuracy from less attention for poor data quality and semantic contexts during data integration and knowledge reasoning. Moreover, the multiple relationships of the concepts are unclear as the multidimensional attributes and association patterns of geo-concepts are not sufficiently analyzed and expressed.The geological model and semantic descriptions are problematic without dynamic trajectories for moving objects and geological events. In this study, a new semi-automatic construction method of geo-ontology was proposed,regarding to geo-contexts based on a multi-dimensional and many-valued concept lattice(MDVCL). A formal concept hierarchy was automatically generated for higher efficiency using the multidimensional and manyvalued concept lattice after data pre-processing and formal context creation of geodatabase. A semantic model of the geo-context-mediated ontologies(GMO) considering both global and local conditions was then constructed by adding four indexes of geo-contexts and dynamic events with OWL(Web Ontology Language) for more accurate formalizing description. The mapping rules were discussed between the concept lattices and the ontologies, and building mappings, in order to achieve straight forward semantic information from the concept lattices. In the end, a construction process was established through three steps, including knowledge preprocessing, multidimensional and many-valued concept lattices and semantic models. A metal mine containing geographic and geological data was selected to build a vein mining ontology for model verification. The results proved that this method could focus on multiple dimensions and complex backgrounds of the data, in order to reduce the risks of semantic errors, increase accuracy and efficiency of mine production, and provide important reference for other geo-ontology domains.
Mine production includes geological survey and excavation, and is the fundamental activity for mine enterprise. Data related to mine production are typically geospatial, showing high space, temporal complexity and multi-scale. Geo-ontology can be applied to clearly describe and formalize geo-concepts, integrate heterogeneous geo-information and share geo-knowledge. However, several problems currently exist in the constructing process of using this new technique: efficiency resulting from extensive human involvement in the building process of geo-ontology, and the low accuracy from less attention for poor data quality and semantic contexts during data integration and knowledge reasoning. Moreover, the multiple relationships of the concepts are unclear as the multidimensional attributes and association patterns of geo-concepts are not sufficiently analyzed and expressed.The geological model and semantic descriptions are problematic without dynamic trajectories for moving objects and geological events. In this study, a new semi-automatic construction method of geo-ontology was proposed,regarding to geo-contexts based on a multi-dimensional and many-valued concept lattice(MDVCL). A formal concept hierarchy was automatically generated for higher efficiency using the multidimensional and manyvalued concept lattice after data pre-processing and formal context creation of geodatabase. A semantic model of the geo-context-mediated ontologies(GMO) considering both global and local conditions was then constructed by adding four indexes of geo-contexts and dynamic events with OWL(Web Ontology Language) for more accurate formalizing description. The mapping rules were discussed between the concept lattices and the ontologies, and building mappings, in order to achieve straight forward semantic information from the concept lattices. In the end, a construction process was established through three steps, including knowledge preprocessing, multidimensional and many-valued concept lattices and semantic models. A metal mine containing geographic and geological data was selected to build a vein mining ontology for model verification. The results proved that this method could focus on multiple dimensions and complex backgrounds of the data, in order to reduce the risks of semantic errors, increase accuracy and efficiency of mine production, and provide important reference for other geo-ontology domains.
引文
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[14]金阳,左万利.多维概念格与多维序列模式的增量挖掘[J].计算机研究与发展,2007,44(11):1816-1824.[Jin Y and Zuo W L.Multi-dimensional concept lattice and incremental discovery of multi-dimensional sequential patterns[J].Journal of Computer Research and Development,2007,44(11):1816-1824.]
[15]郭显娥,王俊红.多维概念格与关联规则发现[J].计算机应用,2010,30(4):1073-1075.[Guo X E,Wang J H.The discovery of multi-dimensional concept lattice and association rules[J].Journal of Computer Applications,2010,30(4):1073-1075.]
[16]刘宏英,郭显娥,胡小珍.多维概念格及其构造算法[J].计算机工程与应用,2012:48(12):96-111.[Liu H Y,Guo X E,Hu X Z.Multidimensional concept lattice and constructing algorithm[J].Computer Engineering and Applications,2012,48(12):96-111.]
[17][德]甘特尔,马垣等译.形式概念分析[M].北京:科学出版社,2007.[Ganter B,translated by Ma H et al.Formal concept analysis[M].Beijing:Science Press,2007.]
[18]Cai G.Contextualization of geospatial database semantics for human-GIS interaction[J].Geoinformatica,2007,11(2):217-237.
[19]Sboui T,Bodeur Y.Modeling the external quality of context to fine-tune context reasoning in geospatial interoperability[C].21stInternational Joint Conference on Artificial Intelligence,Pasadena,USA,2009.
[20]Bouquet P,Giunchiglia F,Harmelen F V,et al.C-OWL:Contextualizing Ontologies[C].The Semantic Web-ISWC2003,Berlin:Springer,2003:164-179.
[21]郭晓波,赵书良,王长宾,等.基于概念格的多值属性关联规则挖掘[J].计算机科学,2014,41(3):267-271.[Guo X B,Zhao S L,Wang C B,et al.Multi-valued attribute association rules mining based on concept lattice[J].Computer Science,2014,41(3):267-271.]
[22]王文超.基于多概念格的复杂领域本体构建研究[D].广州:华南师范大学,2014.[Wang W C.Ontology construction on using multiple concept lattice for complex domain[D].Guangzhou:South China Normal University,2014.]
[23]Sboui T,Bodeur Y.Universal geospatial ontology for the semantic interoperability of data:what are the risks and how to approach them[A].In:Toma?Podobnikar,Marjan?eh(ed).Universal Ontology of Geographic Space:Semantic Enrichment for Spatial Data[M].US:IGI Global,2012:1-27.
[24]李宏伟,陈虎,王振宇等.基于概念格的空间关联规则挖掘优化[J].测绘科学技术学报,2013,30(3):304-307.[Li H W,Chen H,Wang Z Y,et al.Amelioration of spatial association rule mining based on concept lattice[J].Journal of Geomatics Science and Technology,2013,30(3):304-307.]
[25]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 X R,Ren F Y,Lei G P.Research on application of on-line analytical processing systems of domain ontology driven enterprise[J].Journal of Computer Applications,2016,36(1):254-259.]
[2]马小刚.地学数据网络共享与交换研究的新进展[J].国土资源信息化,2006(6):42-43.[Ma X G.The latest progress of research on geoscientific data sharing and exchange[J].Land and Resources Informatization,2006(6):42-43.]
[3]胡玲,李霖,王红.基于本体范畴的地理信息系统语义集成方法[J].测绘科学,2011,36(6):52-55.[Hu L,Li L,Wang H.Methodology of semantic integration of GIS based on category of ontology[J].Science of Surveying and Mapping,2011,36(6):52-55.]
[4]吴孟泉,宋晓东,崔伟宏.基于本体的异构空间数据的集成研究[J].武汉大学学报·信息科学版,2007,32(10):915-918.[Wu M Q,Song X D,Cui W H.On ontology-driven heterogeneous geographic data set integration[J].Geomatics and Information Science of Wuhan University,2007,32(10):915-918.]
[5]徐寅,吉根林,张书亮.基于地理本体的地下管线空间知识表示方法研究[J].南京师范大学学报·自然科学版,2013,36(1):127-132.[Xu Y,Ji G L,Zhang S L.Study on representation method of spatial knowledge on underground pipelines based on Geo-ontology[J].Journal of Nanjing Normal University(Natural Science Edition),2013,36(1):127-132.]
[6]梁汝鹏,李宏伟,马雷雷,等.地理信息服务语义标注原理与关键技术及应用[J].地球信息科学学报,2015,17(4):408-415.[Liang R P,Li H W,Ma L L,et al.Principles,key technologies and their application of semantic annotation of geographical information service[J].Journal of Geo-information Science,2015,17(4):408-415.]
[7]马振刚,李黎黎,许学工.自然地理学的大数据研究[J].地理与地理信息科学,2015,31(3):54-58.[Ma Z G,Li L L,Xu X G.Study on big data of physical geography[J].Geography and Geo-information Science,2015,31(3):54-58.]
[8]徐安建,王海涛,尉伯虎,等.地理本体构建方法研究[J].测绘与空间地理信息,2013,36(7):39-40.[Xu A J,Wang H T,Wei B H,et al.Study on entity based geo-data model[J].Geomatics and Spatial Technology,2013,36(7):39-40.]
[9]滕广青,毕强.基于概念格的异构资源领域本体构建研究[J].现代图书情报技术,2011,27(5):7-12.[Teng G Q,Bi Q.A study on domain ontology construction from heterogeneous resources based on concept lattice[J].New Technology of Library and Information Service,2011,27(5):7-12.]
[10]Haav H M.A semi-automatic method to ontology design by using FCA[C].Czech Republic:International Workshop on Concept Lattices and their Applications,Ostrava,Czech Republic,September,2004.
[11]余霞,刘强,叶丹.基于规则的关系数据库到本体的转换方法[J].计算机应用研究,2008,25(3):766-770.[Yu X.,Liu Q,Ye D.Rule-based approach of transforming relational database to ontology[J].Application Research of Computers,2008,25(3):766-770.]
[12]郭朝敏.姜丽红.蔡鸿明.一种关系数据库到本体的自动构建算法[J].计算机工程与应用,2012,48(7):115-120.[Guo C M,Jiang L H,Cai H M.Automatic method of ontology constructing from relationship database[J].Computer Engineering and Applications,2012,48(7):115-120.]
[13]欧阳纯萍,胡长军,李扬,等.一种基于FCA的面向关系数据库的本体学习方法[J].计算机科学,2011,38(12):167-171.[Ouyang C P,Hu C J,Li Y,et al.Approach of ontology learning from relational database based on FCA[J].Computer Science,2011,38(12):167-171.]
[14]金阳,左万利.多维概念格与多维序列模式的增量挖掘[J].计算机研究与发展,2007,44(11):1816-1824.[Jin Y and Zuo W L.Multi-dimensional concept lattice and incremental discovery of multi-dimensional sequential patterns[J].Journal of Computer Research and Development,2007,44(11):1816-1824.]
[15]郭显娥,王俊红.多维概念格与关联规则发现[J].计算机应用,2010,30(4):1073-1075.[Guo X E,Wang J H.The discovery of multi-dimensional concept lattice and association rules[J].Journal of Computer Applications,2010,30(4):1073-1075.]
[16]刘宏英,郭显娥,胡小珍.多维概念格及其构造算法[J].计算机工程与应用,2012:48(12):96-111.[Liu H Y,Guo X E,Hu X Z.Multidimensional concept lattice and constructing algorithm[J].Computer Engineering and Applications,2012,48(12):96-111.]
[17][德]甘特尔,马垣等译.形式概念分析[M].北京:科学出版社,2007.[Ganter B,translated by Ma H et al.Formal concept analysis[M].Beijing:Science Press,2007.]
[18]Cai G.Contextualization of geospatial database semantics for human-GIS interaction[J].Geoinformatica,2007,11(2):217-237.
[19]Sboui T,Bodeur Y.Modeling the external quality of context to fine-tune context reasoning in geospatial interoperability[C].21stInternational Joint Conference on Artificial Intelligence,Pasadena,USA,2009.
[20]Bouquet P,Giunchiglia F,Harmelen F V,et al.C-OWL:Contextualizing Ontologies[C].The Semantic Web-ISWC2003,Berlin:Springer,2003:164-179.
[21]郭晓波,赵书良,王长宾,等.基于概念格的多值属性关联规则挖掘[J].计算机科学,2014,41(3):267-271.[Guo X B,Zhao S L,Wang C B,et al.Multi-valued attribute association rules mining based on concept lattice[J].Computer Science,2014,41(3):267-271.]
[22]王文超.基于多概念格的复杂领域本体构建研究[D].广州:华南师范大学,2014.[Wang W C.Ontology construction on using multiple concept lattice for complex domain[D].Guangzhou:South China Normal University,2014.]
[23]Sboui T,Bodeur Y.Universal geospatial ontology for the semantic interoperability of data:what are the risks and how to approach them[A].In:Toma?Podobnikar,Marjan?eh(ed).Universal Ontology of Geographic Space:Semantic Enrichment for Spatial Data[M].US:IGI Global,2012:1-27.
[24]李宏伟,陈虎,王振宇等.基于概念格的空间关联规则挖掘优化[J].测绘科学技术学报,2013,30(3):304-307.[Li H W,Chen H,Wang Z Y,et al.Amelioration of spatial association rule mining based on concept lattice[J].Journal of Geomatics Science and Technology,2013,30(3):304-307.]
[25]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 X R,Ren F Y,Lei G P.Research on application of on-line analytical processing systems of domain ontology driven enterprise[J].Journal of Computer Applications,2016,36(1):254-259.]