特定领域本体的构造方法

提出了一种领域本体构造方法OntoMerge,通过该方法构造得到领域本体,再利用领域本体对构件进行本体描述。基于本体、面向服务的构件描述,具有语义推理功能,能极大地提高构件检索的查全率和查准率,并为构件入库、检索、组装等工作奠定基础。     

Domain-specific ontology of botany

Domain-specific ontologies are greatly useful in knowledge acquisition, sharing and analysis. In this paper, botany-specific ontology for acquiring and analyzing botanical knowledge is presented. The ontology is represented in a set of well-defined categories, and each concept is viewed as an instance of certain category. The authors also introduce botany-specific axioms, an integral part of the ontology, for checking and reasoning with the acquired knowledge. Consistency, completeness and redundancy of the axioms are discussed.     

Domain-specific codesign for embedded security

Systems with multiple design domains require codesign of application domains. Dedicated hardware processors implement the application domains and software integrates them. The authors use ThumbPod, a prototype embedded security application, for remote identification applications such as intelligent keys or electronic payments. The device combines security, biometrics, and networking domains. Additional software support consists of a dynamic application download using the Java application manager. Sun's K virtual machine offers an infrastructure for secure code download and execution. The virtual machine also integrates the cryptoprocessor through a native interface.     

Domain-specific Web search with keyword spices

Domain-specific Web search engines are effective tools for reducing the difficulty experienced when acquiring information from the Web. Existing methods for building domain-specific Web search engines require human expertise or specific facilities. However, we can build a domain-specific search engine simply by adding domain-specific keywords, called "keyword spices," to the user's input query and forwarding it to a general-purpose Web search engine. Keyword spices can be effectively discovered from Web documents using machine learning technologies. The paper describes domain-specific Web search engines that use keyword spices for locating recipes, restaurants, and used cars.     

Domain-specific application analysis for customized instruction identification

With the increasing importance of Application Domain Specific Processor (ADSP) design, a significant challenge is to identify special-purpose operations for implementation as a customized instruction. While many methodologies have been proposed for this purpose, they all work for a single algorithm chosen from the target application domain. Such algorithm-specific approaches are not suitable for designing instruction sets applicable to a whole family of related algorithms. For an entire range of related algorithms, this paper develops a methodology for identifying compound operations, as a basis for designing “domain-specific” Instruction Set Architectures (ISAs) that can efficiently run most of the algorithms in a given domain. Our methodology combines three different static analysis techniques to identify instruction sequences common to several related algorithms: identification of (non-branching) instruction sequences that occur commonly across the algorithms; identification of instruction sequences nested within iterative constructs that are thus executed frequently; and identification of commonly-occurring instruction sequences that span basic blocks. Choosing different combinations of these results enables us to design domain-specific special operations with different desired characteristics, such as performance or suitability as a library function. To demonstrate our approach, case studies are carried out for a family of thirteen string matching algorithms. Finally, the validity of our static analysis results is confirmed through independent dynamic analysis experiments and performance improvement measurements.     

面向业务问题求解的知识资源特定领域建模方法

针对企业中解决业务问题时知识资源利用不合理的问题,提出一种面向业务问题求解的知识资源特定领域模型。首先从领域纲要出发,将业务问题求解领域的基本元素描述出来,并详细分析其中对象之间的关系;然后通过在领域模板中建立的问题-知识事件驱动过程链(PK-EPC)模型对问题求解的流程进行格式化,并匹配到相应的知识单元;其次是通过对应的应用模型对业务问题进行分解,并将前面的知识单元与知识载体匹配。根据前面的模型可得出可供企业选择的集成业务活动、知识单元和知识载体的多层次求解方案模型,为企业业务问题求解提供了快捷准确的方法。最后基于Java设计了面向业务问题求解的企业求解方案建模系统,通过实例验证了该模型的可行性。     

特定领域建模的研究和实践

主要讨论分层系统的ＤＳＳＡ,获得此领域的参照构架,并用ＧｅｎＶｏｃａ模型进行描述,最后通过在应用中的实例来讨论有关问题。     

基于领域概念网络的自动批改技术*

随着网络教学的飞速发展和推广应用,作为网络教学核心技术的自动批改技术是近年来讨论的热点问题。针对主观题自动批改技术的难点,提出一种基于带权概念网络进行分层语义相似度计算的主观题自动批改方案,并且通过实际应用验证了该解决方案的可行性,从而在一定程度上解决了自动批改问题。     

基于领域相关词汇提取的特征选择方法

传统文本分类中的文档表示方法一般基于全文本(Bag-Of-Words)的分析,由于忽略了领域相关的语义特征,无法很好地应用于面向特定领域的文本分类任务.本文提出了一种基于语料库对比领域相关词汇提取的特征选择方法,结合SVM分类器实现了适用于特定领域的文本分类系统,能轻松应用到各个领域.该系统在2005年文本检索会议(TREC,Text REtrieval Conference)的基因领域文本分类任务(Genomics Track Categorization Task)的评测中取得第一名.     

一种改进的面向文本的领域概念筛选算法

在语义技术及其应用中,本体学习是一个研究热点,而领域概念筛选则是本体学习的基础。对于领域概念筛选问题,领域一致度与领域相关度相结合的方法效果较好,却也存在信息描述不全的缺点,因此提出了一种针对此问题的改进的领域概念筛选算法。通过计算候选概念之间的语义相似度,识别出低频的具有同义关系和整体一部分关系的词语集,过滤掉部分冗余概念,然后采用改进的领域相关度和领域一致度相结合的公式进行筛选。实验表明,该方法提高了领域概念筛选的有效性。     

基于多策略的专业领域术语抽取器的设计

设计了一个将统计方法与规则方法相结合的专业领域内术语抽取算法。针对专业领域术语的特点,利用多种衡量字符串中各字之间结合“紧密程度”的统计量,先使用阈值分类器抽取出双字候选项;然后再对这些候选项向左右进行一定程度的扩充,从中筛选出符合要求的多字候选项;最后将所得候选项进行过滤,得到最终结果。据此实现了一个以未切分标注的生语料为输入、以专业领域术语为输出的抽取程序,在对多个领域内的语料进行测试后对实验结果进行分析,指出其中存在的问题,对未来的工作作出了展望。     

一种领域软件集成系统的设计技术

针对提高领域软件集成系统的可扩展性、灵活性、可替换性问题,提出一种基于三模型驱动的系统设计技术.方法采用自顶向下的分解原则获取领域模型:利用领域模型和分层技术建立由业务构件和两层框架组成的构件模型;进一步得到基于数据分类、描述、接口的数据模型.三模型的驱动机制保证了在软件生命周期内业务概念的完整性和一致性,解决了扩展性和灵活性问题.最后,给出一个石油钻井模拟软件系统的设计实例,验证了方法的有效性.     

领域科学数据云资源聚合模型

数据中心作为领域科学数据资源的核心设施,正在变得过于复杂、昂贵和低效.大规模领域应用和用户数量的增长,给数据中心的连接性、稳定性和安全性带来严峻的挑战.关于数据中心的资源整合、自动部署以及资源集中化管理正在受到当前学术界和企业界的广泛关注.以实现领域数据中心资源聚合、共享以及统一管理为目的,通过构建领域科学数据云,将多个数据中心连接成一种虚拟的数据网络,以便为领域数据访问、数据集成和数据管理提供环境和服务支持.着重研究了数据云代理模型、异构源共享模型以及资源消息模型.这些模型对于提高数据中心可扩展性和容错性、降低数据中心资源整合成本以及实现从传统数据中心向云化数据中心过渡起到非常关键的作用.最后,将领域科学数据云资源聚合模型引入到油气井科研数据共享服务平台的开发、部署、运行及监控管理中.实践表明,领域科学数据云模型是切实可行的,对于推动领域数据集成、共享、管理研究具有重要的参考意义和应用价值.     

Domain-specific summarization of Life-Science e-experiments from provenance traces

Translational research in Life-Science nowadays leverages e-Science platforms to analyze and produce huge amounts of data. With the unprecedented growth of Life-Science data repositories, identifying relevant data for analysis becomes increasingly difficult. The instrumentation of e-Science platforms with provenance tracking techniques provides useful information from a data analysis process design or debugging perspective. However raw provenance traces are too massive and too generic to facilitate the scientific interpretation of data. In this paper, we propose an integrated approach in which Life-Science knowledge is (i) captured through domain ontologies and linked to Life-Science data analysis tools, and (ii) propagated through rules to produced data, in order to constitute human-tractable experiment summaries. Our approach has been implemented in the Virtual Imaging Platform (VIP) and experimental results show the feasibility of producing few domain-specific statements which opens new data sharing and repurposing opportunities in line with Linked Data initiatives.     

产品评论中领域情感词典的构建

领域情感词典是情感分析最重要的基础。由于产品评论的数量巨大、领域众多,如何自动构建领域情感词典已经成为近年来的一个研究热点。该文提出了一个两阶段的领域情感词典构建算法。第一阶段,利用情感词间的点互信息和上下文约束,使用基于约束的标签传播算法构造基本情感词典;第二阶段,根据情感冲突的频率来识别领域相关情感词,并根据其上下文约束以及修饰的特征完善领域情感词典。实验结果表明,该方法在实际产品评论数据集上取得了较好的效果。
     

一种面向领域本体的教学策略研究方法

教学策略是智能教学系统研究的一个核心问题。论文提出一种基于领域本体的教学策略研究方法,该方法主要包括微教学策略、宏教学策略和教学策略描述语言(TSDL),在领域本体抽象层上实现多个学科教学和个别化教学。该方法在智能教学系统NKI-Tutor中已实现。     

一种基于域知识的协议状态机主动推断算法

现有基于L*算法的协议状态机主动推断方法忽略了协议特有的域知识,将协议报文抽象为相互独立、无意义的符号,并完全随机地生成测试样本进行状态机等价判定,导致产生大量的无效询问和测试样本,在真实网络环境下推断效率较低。在L⁺M算法的基础上提出了一种基于域知识的协议状态机主动推断算法L⁺N,其改进主要体现在:依据会话样本集提取各报文之间的强顺序约束关系来过滤无效的输出询问,构建会话样本集对应的扩展前缀树接受器(Extended Prefix Tree Accepter,EPTA)对输出询问进行预响应,提出了一种基于正例样本变异的等价询问近似判定算法以提升寻找反例的效率。实验结果表明,L⁺N算法能够大幅提高推断效率,并且具有与L⁺M算法相同的推断准确度。     

基于本体的特征知识库研究

使用特征类、特征对象来对零件特征进行表示,从而建立起一种新的概念化特征知识库.     

Domain-specific discrete event modelling and simulation using graph transformation

Graph transformation is being increasingly used to express the semantics of domain-specific visual languages since its graphical nature makes rules intuitive. However, many application domains require an explicit handling of time to accurately represent the behaviour of a real system and to obtain useful simulation metrics to measure throughputs, utilization times and average delays. Inspired by the vast knowledge and experience accumulated by the discrete event simulation community, we propose a novel way of adding explicit time to graph transformation rules. In particular, we take the event scheduling discrete simulation world view and provide rules with the ability to schedule the occurrence of other rules in the future. Hence, our work combines standard, efficient techniques for discrete event simulation (based on the handling of a future event set) and the intuitive, visual nature of graph transformation. Moreover, we show how our formalism can be used to give semantics to other timed approaches and provide an implementation on top of the rewriting logic system Maude.