基于事件本体的突发事件领域知识建模

基于本体的知识建模方法有很多,在某些特定领域采用传统的本体建模方法存在着一些不足。以突发事件领域为例,提出了基于事件本体的知识建模方法。该模型分为上层事件类、下层事件类和事件实例,上层事件类描述的抽象的事件的分类体系,下层事件类是通过事件类关系组成的事件格结构。该模型不仅可以描述事件的时间、地点、对象等要素,还能描述事件类之间的关系。采用本体建模工具Protégé来构建突发事件领域本体,并以“恐怖袭击”作为实例验证了该模型的可用性。研究结果表明,该模型可以清晰地描述事件类的完整性,语义清晰,扩展性强。     

Ontology-based context modeling for emotion recognition in an intelligent web

We describe an ontological model for representation and integration of electroencephalographic (EEG) data and apply it to detect human emotional states. The model (BIO_EMOTION) is an ontology-based context model for emotion recognition and acts as a basis for: (1) the modeling of users’ contexts, including user profiles, EEG data, the situation and environment factors, and (2) supporting reasoning on the users’ emotional states. Because certain ontological concepts in the EEG domain are ill-defined, we formally represent and store these concepts, their taxonomies and high-level representation (i.e., rules) in the model. To evaluate the effectiveness for inferring emotional states, DEAP dataset is used for model reasoning. Result shows that our model reaches an average recognition ratio of 75.19 % on Valence and 81.74 % on Arousal for eight participants. As mentioned above, the BIO-EMOTION model acts like a bridge between users’ emotional states and low-level bio-signal features. It can be integrated in user modeling techniques, and be used to model web users’ emotional states in human-centric web aiming to provide active, transparent, safe and reliable services to users. This work aims at, in other words, creating an ontology-based context model for emotion recognition using EEG. Particularly, this model completely implements the loop body of the W2T data cycle once: from low-level EEG feature acquisition to emotion recognition. A long-term goal for the study is to complete this model to implement the whole W2T data cycle.     

Knowledge and software modeling using UML

Ontology can be considered as a comprehensive knowledge model which enables the developer to practice knowledge, instead of code, reuse. In the development of knowledge-based systems, different modeling languages are employed at different stages of the development process. By using a common modeling language for the knowledge and software models, knowledge instead of software reuse can be achieved. We illustrate the process by first presenting an ontology developed for an industrial domain and then investigate Unified Modeling Language (UML) as an ontology modeling tool. Since any model expressed in UML can be translated into a software model, the transition from the knowledge model to system implementation is better supported with the proposed approach. The industrial domain of selecting a remediation technique for petroleum contaminated sites is adopted for the illustration case study.     

Using a trope-based foundational ontology for bridging different areas of concern in ontology-driven conceptual modeling

In recent years, ontology-driven reference models have gained much attention in the literature due to their potential key role in activities such as complex information modeling and semantic interoperability. The engineering process of these conceptual models should account for different phases addressing different areas of concern. In an initial phase of conceptual domain modeling, the target modeling artifacts should be constructed with the goal of maximizing quality attributes such as expressivity and truthfulness to the represented domain in reality. In a subsequent development phase, the resulting domain models can be used to guide the design decisions in the construction of different implementation artifacts addressing different computational concerns. In this paper, we present a philosophically sound, cognitively-oriented and formally characterized foundational theory of objects and tropes (property-instances). Moreover, we use this theory to bring about engineering contributions to both the aforementioned phases of ontology-driven conceptual modeling. Firstly, we show how this theory has been used to (re)design a system of modeling primitives underlying the conceptual domain modeling language OntoUML. Furthermore, we provide precise directives on how to map conceptual domain models in this language to their implementation in less-expressive computationally-oriented codification languages. In particular, we address here a mapping strategy to OWL (Web Ontology Language) that partially preserves the modal-temporal semantics of OntoUML. Finally, we discuss computational support for the proposed approach in terms of conceptual model construction, automatic transformation and temporal querying.     

Automatically multi-paradigm requirements modeling and analyzing: An ontology-based approach

Requirements engineering (RE) is one of the crucial phases in software engineering (cf. ref. [1]). In the 1995 survey[1], 8000 projects undertaken in the whole country have been examined. The result indicated that one third of the projects were never completed and one half of the rest succeeded only partially. Poor requirements have been identified as the source of such failure (45%), in which the lack of user involvement (13%) and requirements incompleteness (12%) are the two major causes. R…     

Applying ontology-based blog to detect information system post-development change requests conflicts

Post-development change requests are user requirements for information systems changes after development. Conflicts might occur as contradictive or inconsistent relationships between requests and existing system design. Detecting conflicts in post-developmenet change requests is an important task during requests management processes. To address this topic, this article proposes an ontology-based blog for automatically discovering conflicts in the extended use-case models of requests from users. This study proposed an information system maintenance process. The proposed approach applies ontologies to represent domain knowledge. A set of rules are used to detect conflicts. This study developed a prototype and invited two companies to evaluate it. Usage feedback opinions about ontology-based blog from two companies indicated the usefulness. The ontology-based blog is a relatively new approach which bridge requirements blogs with a formal and machine interpretable representational model. The automatic conflicts detection capability of the ontology-based blog can reduce the labor cost in requirements analysis phase.     

面向重用的产品设计过程知识建模与检索

针对传统的产品设计过程知识模型与知识检索方法在提高产品设计过程知识重用性上的不足,提出了多层次多粒度的知识模型以及基于语义的智能检索算法。首先通过分析产品设计过程知识重用的需求,将产品设计过程知识分为项目管理知识、领域知识、产品设计对象知识三类,并建立对应的多层次知识模型。然后在运用本体技术建立产品设计过程知识本体库的基础上,提出了一种基于语义的智能检索算法。最后给出了产品设计过程知识重用模型,并以柴油发动机方案设计为例,证明了该模型的有效性。     

Guidelines for Business Rule Modeling Decisions

Business process models are used heavily in practice as a basis for process improvement, systems development, and understanding business operations. While prior research has identified a clear need for integrating business rules into graphical business process models, there is little guidance on the circumstances under which business rules should be integrated into business process models. Unnecessary integration may hamper business rule reuse, increase business process model complexity, and lead to difficulties with business rule modification, to name a few. Accordingly, it is important to understand when such integration is appropriate. The aim of this article is to address this need for guidance on when business rules should be integrated in process models, and when they should remain separate. To this end, we explain 12 factors posited to influence such modeling decisions, conduct an empirical study to identify their importance, and develop empirically based modeling guidelines that inform business rule modeling decisions.     

基于特征模型和构件语义的概念体系结构设计

特定领域软件体系结构(domain-specific software architecture,简称DSSA)是特定领域开发中的重要资产,而基于特征的领域模型使得从领域需求到DSSA的映射成为可能.引入本体作为特征模型的描述基础,通过该方法得到的领域特征本体将同时作为领域内业务构件的语义描述基础存在.在此基础上,提出了基于特征模型和构件语义的概念体系结构设计方法.该方法综合考虑了特征模型中的共性、可变性、绑定时间以及结构关系、依赖关系等对DSSA设计的影响,同时以构件语义作为特征到概念构件设计的过渡.相关方法已经实现为基于本体的特征建模工具和基于特征模型的体系结构设计工具,为特征驱动的领域开发提供了有力的支持.     

基于本体的民航应急决策知识表达与推理方法研究

针对民航突发事件应急决策知识表达与管理中的问题,利用本体技术在知识获取和建模方面的优势,本文设计了一个基于领域本体的民航突发事件应急决策知识推理模型;以民航突发事件应急预案、应急案例、应急资源和应急规则等应急知识为基础,构建了民航应急管理领域词典,采用领域本体四元组建模方法给出了基于领域词典的本体构建过程;运用SWRL规则语言建立了民航突发事件应急决策所需的基本规则,采用Protégé本体编辑工具和Jena推理机实现了基于本体的规则推理,为民航突发事件应急决策知识的管理与应用提供了良好的方法与技术支持。     

基于本体的网络空间决策支持系统研究*

为了不同的空间决策,往往需要建立相应的空间决策支持系统,在这些空间决策支持系统中,大量的空间数据和模型是可以被重复使用的,因此提出了一种基于本体的空间决策支持系统。该系统能够高效、自动地利用互联网中存在的各类异构空间信息与分析资源来支持空间决策;此外,本系统还提出了一种灵活的体系架构来解决空间决策中存在的语义问题。     

Individual-based modeling of soil organic matter in NetLogo: Transparent,user-friendly,and open

Soil organic matter dynamics are essential for terrestrial ecosystem functions as they affect biogeochemical cycles and, thus, the provision of plant nutrients or the release of greenhouse gases to the atmosphere. Most of the involved processes are driven by microorganisms. To investigate and understand these processes, individual-based models allow analyzing complex microbial systems' behavior based on rules and conditions for individual entities within these systems, taking into account local interactions and individual variations. Here, we present a streamlined, user-friendly and open version of the individual-based model INDISIM-SOM, which describes the mineralization of soil carbon and nitrogen. It was implemented in NetLogo, a widely used and easily accessible software platform especially designed for individual-based simulation models. Including powerful means to observe the model behavior and a standardized documentation, this increases INDISIM-SOM's range of potential uses and users, and facilitates the exchange among soil scientists as well as between different modeling approaches.     

基于本体的特征模型演化的一致性验证

针对特征模型的演化导致特征间的冲突问题, 从特征模型的演化方面进行研究, 提出了一种基于本体的特征模型演化的一致性验证方法。首先采用本体理论方法对特征模型的演化进行分析和建模, 建立本体的特征模型元模型; 其次基于上述元模型, 为网上购物系统实例建立相应的网上购物的领域特征模型, 根据需求裁剪出产品特征模型; 然后在Eclipse集成开发环境下, 通过Jena推理机加载规则和产品特征模型进行一致性验证, 当检测到冲突时, 采用演化策略来消除冲突; 最后通过实例研究说明了该方法的有效性。     

基于本体集成的语义标注模型设计

语义Web的全面实现需借助于语义标注,标注网页信息会涉及到多个本体.据此,通过研究桥本体,提出一个在本体集成的基础上建立起来的多本体语义标注模型.该模型利用桥本体集成顶层本体和多个领域本体,同时借助基于本体的信息抽取技术对网页进行语义标注,并将标注信息存入标注库,使标注信息与网页分离,提高语义检索的效率.通过举例说明了本模型的合理性.     

Automating Mashups for Next-Generation Enterprise Portals

The increasing number of resources available through portals establish a need to tailor information to individual needs and situations. Mashups are tools for dynamically integrating independent applications. For portals, what is needed are means to automatically create personalized mashups that optimally fit a user's information needs in a given situation. At the core of our approach are different ontology-based models that describe the user, the domain, possible information needs in this domain, and personalization rules determining which information to present to which user in which situation.     

“Modeling with tools is easier, believe me”—The effects of tool functionality on modeling grammar usage beliefs

Increasingly, studies are reported that examine how conceptual modeling is conducted in practice. Yet, typically the studies to date have examined in isolation how modeling grammars can be, or are, used to develop models of information systems or organizational processes, without considering that such modeling is typically done by means of a modeling tool that extends the modeling functionality offered by a grammar through complementary features. This paper extends the literature by examining how the use of seven different features of modeling tools affects usage beliefs users develop when using modeling grammars for process modeling. We show that five distinct tool features positively affect usefulness, ease of use and satisfaction beliefs of users. We offer a number of interpretations about the findings. We also describe how the results inform decisions of relevance to developers of modeling tools as well as managers in charge for making modeling-related investment decisions.     

Constraint-driven modeling through transformation

In model-driven software engineering, model transformation plays a key role for automatically generating and updating models. Transformation rules define how source model elements are to be transformed into target model elements. However, defining transformation rules is a complex task, especially in situations where semantic differences or incompleteness allow for alternative interpretations or where models change continuously before and after transformation. This paper proposes constraint-driven modeling where transformation is used to generate constraints on the target model rather than the target model itself. We evaluated the approach on three case studies that address the above difficulties and other common transformation issues. We also developed a proof-of-concept implementation that demonstrates its feasibility. The implementation suggests that constraint-driven transformation is an efficient and scalable alternative and/or complement to traditional transformation.     

Recursive approach to combine expert knowledge and data-driven RSW weldability certification decision making process

Data-driven techniques have shown promising results in the analysis and understanding of complex welding processes. Data analytics play a significant role to turn data into valuable insights to assist in the weldability certification decision-making for Resistance Spot Welding (RSW) as well. However, to successfully perform the associated data analytics, domain knowledge is essential to construct more ‘sense-making’ analytics models, as often the models cannot properly capture the nuances of the domain and do not properly indicate the relationship among the RSW concepts and parameters. Thus, machine learning models developed from rough experimental data often do not provide models meaningful and sensible to the domain expert. In this article, we employ a recursive approach between the domain experts and data-driven models so that the knowledge of the domain experts can be integrated into the weldability certification decision-making process. An ontology-based semantic knowledge framework supports this recursive communication while helping the experts to instil more confidence in the developed analytics models. The collaborative and recursive approach implemented in this study helps the domain experts to tap into their domain knowledge and form expert opinions using the formalized semantic RSW concepts and decision rules. The expert opinions are then used to learn new knowledge about the RSW domain and transform the RSW datasets by incorporating significant features that were not included in the earlier models. The transformed datasets help us to develop improved machine learning models, which in turn work as a new source of semantic knowledge, as we have discovered through our pilot implementation.     

A comprehensive modeling framework for collaborative networked organizations

Collaborative networked organizations (CNOs) are complex entities whose proper understanding, design, implementation, and management require the integration of different modeling perspectives. A large number of modeling tools and theories that have been developed in other disciplines have a potential applicability in this domain. Therefore, an identification of the most promising approaches is made and mapped into four dimensions of an endogenous perspective of collaborative networked organizations: structural, componential, functional, and behavioral. But a comprehensive modeling of such complex dynamic systems requires also an exogenous perspective, the life cycle dimension, and a stratification of models according to the modeling purpose. Thus a comprehensive modeling framework is therefore proposed as a first step towards the elaboration of a reference model for collaborative networks.