基于本体的产品设计知识表示研究

针对目前的产品设计知识表示模型或是只局限于产品设计的某一阶段,或是局限于某一设计领域,对产品设计知识的概念存在着分类不清等不足,文中提出一种产品设计知识本体构建方法,并构建基于本体的产品设计知识表示模型。通过分析产品设计知识本体产生的知识概念、属性及知识概念间关系,形式化地定义和描述表示产品设计领域所包含的知识资源,提高企业产品设计知识共享和重用效率。以色选机设计知识表示为例,验证了所提出模型的有效性。     

基于多层领域本体的知识表示通用模型研究

随着复杂信息系统涉及的知识领域越来越广泛,传统的基于领域本体以及基于关键词的知识表示模型,当处理多领域异构知识的共享与重构时,表现出异构信息有效组织及准确检索的不足。针对此问题,提出了基于多层领域本体的知识表示通用模型,借鉴顶层本体提供的上层语义知识,整合各领域的本体知识,并详细分析了由顶层本体、上层本体、应用本体、实例本体组成的多层领域本体的各层本体的构建流程。仿真实验通过与基于传统领域本体以及基于关键词的知识表示模型的对比分析,分别于一个以及多个领域知识的视角下,验证了基于多层领域本体的知识表示通用模型的有效性。     

基于本体的产品知识表达

产品开发过程分工的加强、市场和全球化竞争的激烈都要求工厂能够更迅速地生产更廉价和质量更高的产品，而这需要一个更有效并且强有力的产品知识管理系统，以支持产品知识的表达、重用、共享和交流等．研究了产品知识表达的模型，即S—B—F，结合本体描述语言构建了流本体和功能本体，设计出基于本体的产品知识表达，并进一步提出了可行的应用模型。     

基于细胞元本体的标准件库资源共享研究

针对目前标准件库不支持异构CAD系统和标准件信息不完整两个主要问题,提出了一种基于细胞元本体的标准件库资源共享方法。该方法使用Web本体描述语言(Web Ontology Language,OWL)表示细胞元本体模型,制定语义映射规则,以细胞为转换单元,屏蔽了信息表示的异构性,使应用本体和细胞元本体成为具有语义关系的逻辑上的整体,实现了异构CAD系统对标准件库的共享及异构数据的实时转换。该方法应用在Pro/E,UG和CATIA3个CAD平台的同步协同设计中,证明了其可行性。     

Building a global normalized ontology for integrating geographic data sources

Nowadays, the proliferation of geographic information systems has caused great interest in integration. However, an integration process is not as simple as joining several systems, since any effort at information sharing runs into the problem of semantic heterogeneity, which requires the identification and representation of all semantics useful in performing schema integration. On several research lines, including research on geographic information system integration, ontologies have been introduced to facilitate knowledge sharing among various agents. Particularly, one of the aspects of ontology sharing is performing some sort of mapping between ontology constructs. Further, some research suggests that we should also be able to combine ontologies where the product of this combination will be, at the very least, the intersection of the two given ontologies. However, few approaches built integrations upon standard and normalized information, which might improve accuracy of mappings and therefore commitment and understandability of the integration. In this work, we propose a novel system (called GeoMergeP) to integrate geographic sources by formalizing their information as normalized ontologies. Our integral merging process—including structural, syntactic and semantic aspects—assists users in finding the more suitable correspondences. The system has been empirically tested in the context of projects of the Italian Institute for Environmental Protection and Research (ISPRA, ex APAT), providing a consistent and complete integration of their sources.     

基于本体的城市交通的知识分析和推理

以城市交通为研究和应用背景，基于本体模型的知识表示技术，建立城市交通本体。对城市交通领域知识进行规范描述，详细描述了定义类层次及类的属性和关系，以及实例的基本规则，并从领域知识中提取出类内公理和类间公理，建立公理库，用于领域知识的一致性分析和知识推理。解决了语义层次上信息共享和交互的问题，为上海城市交通信息网格的交通信息服务提供语义支撑。     

Learning concept hierarchies from textual resources for ontologies construction

Ontologies play a very important role in knowledge management and the Semantic Web, their use has been exploited in many current applications. Ontologies are especially useful because they support the exchange and sharing of information. Ontology learning from text is the process of deriving high-level concepts and their relations. An important task in ontology learning from text is to obtain a set of representative concepts to model a domain and organize them into a hierarchical structure (taxonomy) from unstructured information. In the process of building a taxonomy, the identification of hypernym/hyponym relations between terms is essential. How to automatically build the appropriate structure to represent the information contained in unstructured texts is a challenging task. This paper presents a novel method to obtain, from unstructured texts, representative concepts and their taxonomic relationships in a specific knowledge domain. This approach builds a concept hierarchy from a specific-domain corpus by using a clustering algorithm, a set of linguistic patterns, and additional contextual information extracted from the Web that improves the discovery of the most representative hypernym/hyponym relationships. A set of experiments were carried out using four different corpora. We evaluated the quality of the constructed taxonomies against gold standard ontologies, the experiments show promising results.     

CFinder: An intelligent key concept finder from text for ontology development

Key concept extraction is a major step for ontology learning that aims to build an ontology by identifying relevant domain concepts and their semantic relationships from a text corpus. The success of ontology development using key concept extraction strongly relies on the degree of relevance of the key concepts identified. If the identified key concepts are not closely relevant to the domain, the constructed ontology will not be able to correctly and fully represent the domain knowledge. In this paper, we propose a novel method, named CFinder, for key concept extraction. Given a text corpus in the target domain, CFinder first extracts noun phrases using their linguistic patterns based on Part-Of-Speech (POS) tags as candidates for key concepts. To calculate the weights (or importance) of these candidates within the domain, CFinder combines their statistical knowledge and domain-specific knowledge indicating their relative importance within the domain. The calculated weights are further enhanced by considering an inner structural pattern of the candidates. The effectiveness of CFinder is evaluated with a recently developed ontology for the domain of ‘emergency management for mass gatherings’ against the state-of-the-art methods for key concept extraction including—Text2Onto, KP-Miner and Moki. The comparative evaluation results show that CFinder statistically significantly outperforms all the three methods in terms of F-measure and average precision.     

基于功能本体的设计知识共享平台

为弥补制造业中设计知识在共享和重用方面的缺陷,提出一种基于功能本体的设计知识共享策略。使用功能本体实现现有产品结构到其功能的映射,利用功能分解树表达产品的设计原理。首先,介绍了功能本体的基本框架;然后,分析了功能分解树在产品设计中的作用;最后,通过实现一个家电领域设计知识共享平台,验证所提出的共享策略的可行性。实验结果表明,该策略能有效实现制造业设计知识的信息检索、共享和重用,可以缩短产品的开发周期。     

Enabling information sharing within organizations

Organizations which have invested heavily in Enterprise Resource Planning (ERP) systems, intranets and Enterprise Information Portals (EIP) with standardized workflows, data definitions and a common data repository, have provided the technlogical capability to their workgroups to share information at the enterprise level. However, the responsibility of populating the repository with relevant and high quality data required for customized data analyses is spread across workgroups associated with specific business processes. In an information interdependent setting, factors such as short-term organizational focus and the lack of uniformity in information management skills across workgroups can act as impediments to information sharing. Using an analytical model of information exchange between two workgroups, we study the impact of measures (e.g., creating a perception of continuity and persistence in interactions, benefit sharing, etc.) on the performance of the workgroups and the organization. The model considers a setting we describe as information complementarity, where the payoff to a workgroup depends not only on the quality of its own information, but also on that of the information provided by other workgroups. We show how a long-term vision combined with homogeneity in information management capabilities across workgroups can lead to organizationally desirable levels of information exchange, and how benefit sharing can either help or hurt individual and organizational information exchange outcomes under different circumstances. Our analysis highlights the need for appropriate organizational enablers to realize the benefits of enterprise systems and related applications.

Distributed ontology building as practical work

Ontologies – a form of structured and logically related knowledge or classification hierarchy embedded in a computer system – are regarded by many scientists as having enormous promise for the consistent use and re-use of data. To realise this promise, however, is not straightforward. In this paper, based on ethnographic observation, we argue that the challenges for ontology building are ‘social’ as much as they are technical. By this we mean the routine work undertaken in the building process and the problems and difficulties entailed can be understood in terms of the practices of knowledge workers and the practical nature of ‘sorting things out’. Getting a better sense of how, in practise, this work gets done gives a sense of the main challenges of building successful ontologies and how this impacts on the design of tool support. In considering the practices of one group in particular, we try to show how, for members, the technical problems of determining what classification structure is appropriate, and what its boundaries might be, depend substantially on assumptions about the ‘community’ and its interests and purposes. This ‘turn to the social’ has ramifications for the understanding of ontology building and use. Specifically, ‘modelling’ approaches to ontology building tell us little about the practical organisation of the work and how this relates to the prospect of successful sharing. Ethnographic enquiry may reveal important issues that are otherwise missed.     

Enriching standards-based digital thread by fusing as-designed and as-inspected data using knowledge graphs

Realizing the digital thread is essential for linking and orchestrating data across the product lifecycle in smart manufacturing. Linking heterogeneous lifecycle data is critical to maintain associativity and traceability in a digital thread. Recently, researchers have successfully leveraged ontology models with knowledge graphs in engineering domains for threading different lifecycle data. One of the most successful of such efforts is OntoSTEP which enables the formal capture of information embedded in the STandard for Exchange of Product model data (STEP) data representation, or ISO 10303. Meanwhile, an emerging inspection standard, called the Quality Information Framework (QIF), has garnered significant attention as it can bring quality information into the digital thread. Implementing more automated methods for product quality assurance is challenging due to the lack of unified information models from design to inspection. To this end, we propose an approach to fuse as-designed data represented in STEP and as-inspected data represented in QIF in a standards-based digital thread based on ontology with knowledge graphs. Specifically, we present an automated pipeline for generating knowledge graphs representing STEP and QIF data, a mapping implementation to integrate STEP and QIF knowledge graphs, and rules and queries to demonstrate the integration’s potential for better decision making with respect to product quality assurance.     

产品设计过程中的感知建模研究

分析了设计过程中的社会互动因素,建立了产品的多感知因素设计过程体系结构。在此基础上,应用基于问题的推理系统作为概念结构,建立了感知模型,并运用社会网络和层次聚类方法进行应用分析,以全面理解和有效管理设计过程。     

基于本体的Web文本挖掘与信息检索

针对传统Web文本挖掘技术缺少语义理解能力的不足,提出并实现一种基于本体的Web文本挖掘模型,即利用基于本体概念体系的向量空间模型替代传统的向量空间模型来表示文档,在此基础上进行Web文本挖掘,并给出一种集成语义信息检索的设计。实验结果初步验证了本体模型在Web文本挖掘技术上应用的可行性。     

面向GIS多重表达的本体语义模型

多重表达是地理信息弹性存取和集成分析的一个内在要求,它实质上提供了一个多尺度、多应用主题的信息集成机制。多重表达的概念建模需要在高度抽象的地理概念层次上实现地理信息一体化的弹性表达,而不是局限于数据库中几何多样性的一致性描述。基于本体的地理信息建模更贴近于认知模型,还有助于模型语义的表达以及基于语义的信息集成和共享。论文探讨了基于本体的地理概念表达与GIS语义的形式化,并通过多重表达上下文的抽象以及本体逻辑基础的上下文扩展,给出一个支持GIS多重表达的本体语义模型,该模型能够为多重表达数据库的实现提供一个易于理解和共享的形式化基础。     

域信息共享的方法在蒙汉机器翻译中的应用

蒙汉翻译属于低资源语言的翻译,面临着平行语料资源稀缺的困难,为了缓解平行语料数据稀缺和词汇表受限引发的翻译正确率低的问题,利用动态的数据预训练方法ELMo（Embeddings from Language Models）,并结合多任务域信息共享的Transformer翻译架构进行蒙汉翻译。利用ELMo（深层语境化词表示）进行单语语料的预训练。利用FastText词嵌入算法把蒙汉平行语料库中的上下文语境相关的大规模文本进行预训练。根据多任务共享参数以实现域信息共享的原理,构建了一对多的编码器-解码器模型进行蒙汉神经机器翻译。实验结果表明,该翻译方法比Transformer基线翻译方法在长句子输入序列中可以有效提高翻译质量。     

基于任务结构模型的多Agent产品并行开发体系

为了促进产品并行开发,文章提出了一种用于描述基于领域的任务分解、任务之间的约束关系及任务与产品信息之间对应关系的任务结构模型,设计了表示语言ＣＲＬＥ以定义领域共享本体论和任务结构模型。在此基础上构建了多Ａｇｅｎｔ产品并行开发体系,包括由多个协作Ａｇｅｎｔ和一个协作促进器组成的Ａｇｅｎｔ联邦、系统服务Ａｇｅｎｔ和领域服务Ａｇｅｎｔ,并提供了协调机制。     

PRONTO: An ontology for comprehensive and consistent representation of product information

Nowadays, it is quite common for collaborating organizations (or even different areas within a company) to develop and maintain their own product model. This situation leads to information duplication and its associated problems. Besides, traditional product models do not properly handle the high number of variants managed in today competitive markets. In addition, there is a need for an integrated product model to be shared by all the organizations participating in global supply chains (SCs) or all the areas within a company. One way to reach an intelligent integration among product models is by means of an ontology. PRoduct ONTOlogy (PRONTO) is an ontology for the product modeling domain, able to efficiently handle product variants. It defines and integrates two hierarchies to represent product information: the abstraction hierarchy (AH) and the structural one (SH). This contribution presents a ConceptBase formal specification of PRONTO that focuses on the structural hierarchy of products. This hierarchy is a tool to handle product information associated with the multiple available recipes or processes to manufacture a particular product or a set of similar products. The formal specification presented in the paper also includes mechanisms to infer structural information from the explicit knowledge represented at each of the AH levels: Family, VariantSet and Product. This proposal efficiently handles a great number of variants and allows representing product information with distinct granularity degrees, which is a requirement for planning activities taking place at different time horizons. PRONTO easily manages crucial features that should be taken into account in a product representation, such as the efficient handling of product families and variants concepts, composition and decomposition structures and the possibility of specifying constraints. To demonstrate the semantic expressiveness of the proposed ontology a food industry related case-study is addressed and discussed in detail.     

基于图解特征语义认知的产品设计过程知识模型

针对产品造型设计过程知识表征,提出基于图解语义认知的产品设计过程知识模 型。分析产品的本体语义及产品设计过程知识,结合可拓学基元理论构建产品设计过程的知识 表征基元模型,提出可拓原点基元及可拓向量概念,实现设计过程--设计生长、设计收敛及 设计优化的知识表征。在产品设计过程知识基元表征模型基础上,提出基于图解语义的实例库 聚类方法模型。以机床装备造型设计为例,验证了该方法的可行性,为产品造型设计提供一种 形式化与量化相结合的设计参考方法。