开放环境下本体演化语义冲突的检测与诊断研究
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摘要
本体演化是为适应变更而对本体做出的及时变更,并要保持变更后本体及其相关应用的一致性。纵观近年来本体演化研究,现有方法和工具大多以集中式环境为前提,但在Web这样开放的动态环境中显露出一些难于解决的问题,如全局知识、语义冲突和不可计算性等。开放环境下的本体演化客观上需要对一致性进行检测、定位和甚至是修复的非标准推理技术。
如何检测和诊断变更序列之间的语义冲突是开放环境下的本体演化面临的主要任务。本论文在总结本体演化研究现状的基础上,将深入研究本体一致性非标准推理方法,以及开放环境下多人修改本体条件下的变更序列语义冲突检测方法和冲突诊断方法。本论文主要包含以下几部分研究内容：
(1)提出一种基于Alloy的本体一致性非标准推理方法。该方法首先对本体文件进行解析,提出转换算法,再以解析结果作为输入,生成用Alloy语言描述的本体模型,根据模型的推理结果对本体的一致性进行判断。该方法能够弥补现有方法不能进行ABox推理的不足,并且对于不满足一致性推理的本体能够给出反例,为查找不一致问题的根源提供依据。
(2)提出一种改进的基于SAT的本体一致性非标准推理方法。这种方法首先定义一种基于逻辑的中间语言,并给出OWL本体语言与中间语言之间的转换规则,最后将SAT求解器计算的实验数据与已有方法进行对比,说明该方法支持更大规模的本体推理。对于找不到可满足解的本体,通过计算最小不可满足集来查找不可满足的原因。
(3)提出开放环境下本体演化变更序列的冲突检测算法。本研究内容在定义本体演化的基本概念和关系的基础上,对开放环境下本体变化序列之间的冲突进行研究讨论。提出冲突分类、冲突检测方法。这种方法按照冲突产生的范围将冲突分为序列内部的不一致冲突、变更序列之间的直接冲突和序列之间的不一致冲突。针对不同的冲突类型分别给出不同的冲突检测算法,并证明算法的正确性。该方法不仅能够检测出冲突,而且能在出现冲突的情况下找到最大一致变更子序列,保证演化的顺利进行。
(4)提出开放环境下本体演化变更序列语义冲突诊断算法。方法中引入冲突变更序列矩阵、冲突序列集合、最小碰集序列等概念,对本体演化中的变更序列进行描述,进一步计算最小碰集序列集合。再引入贝叶斯概率公式计算最小碰集序列集合中概率,进而进行排序,用排序结果表示最小碰集序列集合中的最小碰集序列导致冲突的可能性。
(5)设计并实现一个支持开放环境下本体演化的原型系统。该系统能够对开放环境下变更序列内部与变更序列之间的冲突进行检测,并针对语义冲突进行冲突诊断,保证本体演化的顺利进行。更进一步,能够对变更后的本体进行一致性检测,保证演化本体的正确性。
Ontology evolution is the timely adaptation of an ontology to the arisen changes and the consistent propagation of these changes to dependent artifacts. A survey of the state-of-art approaches to ontology evolution shows that most methods and tools were assumed to work in a centralized environment. However, some problems such as global knowledge, semantic conflicts and intractability arise from this assumption in an open dynamic environment like the Semantic Web. Evolving ontologies in an open environment neccesarily demands for non-standard reasoning technology of consistency checking, inconsistency localization and repair.
Semantic conflicts detection and diagnosis are the major tasks for ontology evolution in open environment. On the basis of surveying the research on ontology evolution, this thesis focuses on the non-standard reasoning services for ontology consistency checking, semantic conflicts detection and diagnosis approaches to coping with the conflicting change sequences when multiple users independently make changes to an ontology in an open environment. The main contents are as followings:
(1) We propose non-standard reasoning approaches for evolving ontology. In this method, the ontology document is analyzed by Jena, the results of which will be used as the inputs of the transformation algorithms, which are used to transferred the OWL ontology into Alloy model. Then Alloy Analyzer is used to judge the consistency. This method can remedy the deficiency of current reasoning methods of lacking ABox reasoning. Further, the counter-examples of the inconsistent ontologies are given to provide evidences to pinpoint the causes.
(2) To improve the scale of the reasoning ontology, we present an improved SAT-based non-standard reasoning method for checking ontology consistency. In doing so, we define a logic based intermediate core-language, and present the transformation rules from OWL ontology language to the intermediate core-language. An experimental comparison shows that the proposed method can handle middle-sized ontologies. For the unsatisfiable ontology, we find out the cause by computing the minimal unsatisfiable sets.
(3) We present a new method to detect conflicts for ontology evolution in open environment. The definitions of concepts and relationships of ontology evolution are the foundation of the research. We classifies conflicts as three groups:internal inconsistencies conflicts in change sequence, direct conflicts between the sequences and Inconsistent conflict between the sequences. For different conflicts, high effective detecting algorithms are presented with evaluation. This method can not only can find out the conflicts, but it also can get the maximum consistent changing sequence in a conflict situation to keep the evolution running.
(4) We present a the semantic conflicts diagnosis approach, which focus on of the changing sequences of ontology evolution in open environment. This approach introduces conflict matrix to model the changing sequences, and uses statistical methods to get the minimal hitting sequence set of the matrix as the candidates for the diagnosis. By quantifying the Bayes reasoning mechanism with probability information, the diagnosis results can be measured quantitatively. It updates probability of each candidate, and the possibility rank result indicates the likelihood of the candidates to lead to the conflict.
(5) To support the ontology evolution in an open environment, we designed and realized a prototype system. The system can detect and diagnosis the conflicts of the ontology evolution. Further, it provides consistency reasoning mechanism to prove the correctness of changing ontologies.
如何检测和诊断变更序列之间的语义冲突是开放环境下的本体演化面临的主要任务。本论文在总结本体演化研究现状的基础上,将深入研究本体一致性非标准推理方法,以及开放环境下多人修改本体条件下的变更序列语义冲突检测方法和冲突诊断方法。本论文主要包含以下几部分研究内容：
(1)提出一种基于Alloy的本体一致性非标准推理方法。该方法首先对本体文件进行解析,提出转换算法,再以解析结果作为输入,生成用Alloy语言描述的本体模型,根据模型的推理结果对本体的一致性进行判断。该方法能够弥补现有方法不能进行ABox推理的不足,并且对于不满足一致性推理的本体能够给出反例,为查找不一致问题的根源提供依据。
(2)提出一种改进的基于SAT的本体一致性非标准推理方法。这种方法首先定义一种基于逻辑的中间语言,并给出OWL本体语言与中间语言之间的转换规则,最后将SAT求解器计算的实验数据与已有方法进行对比,说明该方法支持更大规模的本体推理。对于找不到可满足解的本体,通过计算最小不可满足集来查找不可满足的原因。
(3)提出开放环境下本体演化变更序列的冲突检测算法。本研究内容在定义本体演化的基本概念和关系的基础上,对开放环境下本体变化序列之间的冲突进行研究讨论。提出冲突分类、冲突检测方法。这种方法按照冲突产生的范围将冲突分为序列内部的不一致冲突、变更序列之间的直接冲突和序列之间的不一致冲突。针对不同的冲突类型分别给出不同的冲突检测算法,并证明算法的正确性。该方法不仅能够检测出冲突,而且能在出现冲突的情况下找到最大一致变更子序列,保证演化的顺利进行。
(4)提出开放环境下本体演化变更序列语义冲突诊断算法。方法中引入冲突变更序列矩阵、冲突序列集合、最小碰集序列等概念,对本体演化中的变更序列进行描述,进一步计算最小碰集序列集合。再引入贝叶斯概率公式计算最小碰集序列集合中概率,进而进行排序,用排序结果表示最小碰集序列集合中的最小碰集序列导致冲突的可能性。
(5)设计并实现一个支持开放环境下本体演化的原型系统。该系统能够对开放环境下变更序列内部与变更序列之间的冲突进行检测,并针对语义冲突进行冲突诊断,保证本体演化的顺利进行。更进一步,能够对变更后的本体进行一致性检测,保证演化本体的正确性。
Ontology evolution is the timely adaptation of an ontology to the arisen changes and the consistent propagation of these changes to dependent artifacts. A survey of the state-of-art approaches to ontology evolution shows that most methods and tools were assumed to work in a centralized environment. However, some problems such as global knowledge, semantic conflicts and intractability arise from this assumption in an open dynamic environment like the Semantic Web. Evolving ontologies in an open environment neccesarily demands for non-standard reasoning technology of consistency checking, inconsistency localization and repair.
Semantic conflicts detection and diagnosis are the major tasks for ontology evolution in open environment. On the basis of surveying the research on ontology evolution, this thesis focuses on the non-standard reasoning services for ontology consistency checking, semantic conflicts detection and diagnosis approaches to coping with the conflicting change sequences when multiple users independently make changes to an ontology in an open environment. The main contents are as followings:
(1) We propose non-standard reasoning approaches for evolving ontology. In this method, the ontology document is analyzed by Jena, the results of which will be used as the inputs of the transformation algorithms, which are used to transferred the OWL ontology into Alloy model. Then Alloy Analyzer is used to judge the consistency. This method can remedy the deficiency of current reasoning methods of lacking ABox reasoning. Further, the counter-examples of the inconsistent ontologies are given to provide evidences to pinpoint the causes.
(2) To improve the scale of the reasoning ontology, we present an improved SAT-based non-standard reasoning method for checking ontology consistency. In doing so, we define a logic based intermediate core-language, and present the transformation rules from OWL ontology language to the intermediate core-language. An experimental comparison shows that the proposed method can handle middle-sized ontologies. For the unsatisfiable ontology, we find out the cause by computing the minimal unsatisfiable sets.
(3) We present a new method to detect conflicts for ontology evolution in open environment. The definitions of concepts and relationships of ontology evolution are the foundation of the research. We classifies conflicts as three groups:internal inconsistencies conflicts in change sequence, direct conflicts between the sequences and Inconsistent conflict between the sequences. For different conflicts, high effective detecting algorithms are presented with evaluation. This method can not only can find out the conflicts, but it also can get the maximum consistent changing sequence in a conflict situation to keep the evolution running.
(4) We present a the semantic conflicts diagnosis approach, which focus on of the changing sequences of ontology evolution in open environment. This approach introduces conflict matrix to model the changing sequences, and uses statistical methods to get the minimal hitting sequence set of the matrix as the candidates for the diagnosis. By quantifying the Bayes reasoning mechanism with probability information, the diagnosis results can be measured quantitatively. It updates probability of each candidate, and the possibility rank result indicates the likelihood of the candidates to lead to the conflict.
(5) To support the ontology evolution in an open environment, we designed and realized a prototype system. The system can detect and diagnosis the conflicts of the ontology evolution. Further, it provides consistency reasoning mechanism to prove the correctness of changing ontologies.
引文
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