Thesaurus-based approach for building domain ontology with a case study of military aircraft prototype ontology construction

To alleviate the amount of work involved in constructing a domain ontology, starting with the base of an existing terminological-rich thesaurus is better than starting from scratch. With a case study of reengineering the Defense Science and Technology Thesaurus into a prototype military aircraft ontology, a four-phase thesaurus-based methodology is introduced and investigated, which consists of identifying the application purpose, overall design, designing in detail and evaluation. Designing in detail is the core step, converting the terms and semantic relationships of the thesaurus into an ontology and supplementing richer semantic relationships. The resulting prototype ontology includes 87 concepts and 34 relationships, and can be extended and scaled up to a full-fledged domain ontology in the future. Eight universal genres of relationships of this ontology are preliminarily summarized and analyzed, including equivalent relationships, approximate relationships, generic/abstract relationships, part/whole relationships, cause/effect relationships, entity/location relationships etc., and the normalization of semantic relationships is critical to the merging and reusing of follow-up multiple ontologies.

Incorporating Domain Knowledge into Data Mining Process:An Ontology Based Framework

With the explosive growth of data available, there is an urgent need to develop continuous data mining which reduces manual interaction evidently. A novel model for data mining is proposed in evolving environment. First, some valid mining task schedules are generated, and then au tonomous and local mining are executed periodically, finally, previous results are merged and refined. The framework based on the model creates a communication mechanism to in corporate domain knowledge into continuous process through ontology service. The local and merge mining are transparent to the end user and heterogeneous data ,source by ontology. Experiments suggest that the framework should be useful in guiding the continuous mining process.

Heuristic web service composition method based on domain ontology

In order to realize automatic web service composition, a heuristic web service composition method based on domain ontology is proposed. First, this method integrates the domain ontology and the artificial intelligence （AI） planning algorithm. Then, it uses the domain ontology and its reasoning capability to infer the semantic relationship among parameters. Finally, it transforms the web service composition problem into the planning problem based on the AI planning heuristic algorithm. The preliminary experimental results show that the above method compensates for the lack of semantics in the previous AI planning method and it can satisfy the requirements of quality and efficiency of composition, thus generating composite web services according to customer requirements automatically and efficiently.

Large-Scale Ontology Development and Agricultural Application Based on Knowledge Domain Framework

The key activity to build semantic web is to build ontologies. But today, the theory and methodology of ontology construction is still far from ready. This paper proposed a theoretical framework for massive knowledge management- the knowledge domain framework （KDF）, and introduces an integrated development environment （IDE） named large-scale ontology development environment （LODE）, which implements the proposed theoretical framework. We also compared LODE with other popular ontology development environments in this paper. The practice of using LODE on management and development of agriculture ontologies shows that knowledge domain framework can handle the development activities of large scale ontologies. Application studies based on the described briefly. principle of knowledge domain framework and LODE was

Traditional Chinese Medicine(TCM)Domain Ontology:Current Status and Rethinking for the Future Development

The past twenty years have seen the increasingly important role of ontology in traditional Chinese medicine(TCM).However,the development of TCM ontology faces many challenges.Since the epistemologies dramatically differ between TCM and contemporary biomedicine,it is hard to apply the existing top-level ontology mechanically.“Data silos”are widely present in the currently available terminology standards,term sets,and ontologies.The formal representation of ontology needs to be further improved in TCM.Therefore,we propose a unified basic semantic framework of TCM based on in-depth theoretical research on the existing top・level ontology and a re-study of important concepts in TCM.Under such a framework,ontologies in TCM subdomains should be built collaboratively and be represented formally in a common format.Besides,extensive cooperation should be encouraged by establishing ontology research communities to promote ontology peer review and reuse.

Domain ontology driven composable simulation framework

The simulation composability is one of important development directions in simulation domain. The key issue is the semantic composability. Currently there is no feasible approach to realize the effective semantic representation and composition of simulation components. Based on domain knowledge and Web Ontology Language (OWL), this paper proposes a composable simulation framework, which includes conceptual model semantics, model components semantics, model framework semantics, and simulation scenario semantics. Additionally, all the semantics are utilized in the model components development process, the simulation system development process, and the simulation system execution process respectively. The consistency checking among those semantics is also proposed. The detailed mapping processes between different semantic models can help to build the domain ontology driven composable simulation system.

Metadata Extended Model Based On Geological Domain Ontology

The current metadata modeling techniques can not meet the needs of knowledge conception expression, knowledge organization, and metadata semantic consistency in geological domain. This paper introduces ontology and integrates this theory to geological domain metadata modeling. It adopts the first order logic equivalent algorithm and defines the metadata extended model as a quaternion group which is consists of geological term set, geological term definition set, attribute definition set and instance set. It also provides the formal description of each set. Finally the five steps for building geological domain metadata extended model are given. The result presents that this model not only provides the content standards for geological domain knowledge representation and knowledge organization, but also provides the basis for geological domain multi-source data and historical data integration and application in semantic consistency.

An Ontology-Based Question Answering System for University Admissions Advising

Question-Answer systems are now very popular and crucial to support human in automatically responding frequent questions in manyfields.However,these systems depend on learning methods and training data.Therefore,it is necessary to prepare such a good dataset,but it is not an easy job.An ontol-ogy-based domain knowledge base is able to help to reason semantic information and make effective answers given user questions.This study proposes a novel chatbot model involving ontology to generate efficient responses automatically.A case study of admissions advising at the International University–VNU HCMC is taken into account in the proposed chatbot.A domain ontology is designed and built based on the domain knowledge of university admissions using Protégé.The Web user interface of the proposed chatbot system is developed as a prototype using NetBeans.It includes a search engine reasoning the ontology and generat-ing answers to users’questions.Two experiments are carried out to test how the system reacts to different questions.Thefirst experiment examines questions made from some templates,and the second one examines normal questions taken from frequent questions.Experimental results have shown that the ontology-based chatbot can release meaningful and long answers.The results are analysed to prove the proposed chatbot is usable and promising.

An Approach towards Goal-Oriented Requirements Ontology: Consistency and Completeness Based Requirements Analysis

The paper presents a new approach to managing software requirement elicitation techniques with a high level of analyses based on domain ontology techniques, where we established a mapping between user scenario, structured requirement, and domain ontology techniques to improve many attributes such as requirement consistency, completeness and eliminating duplicate requirements to reduce risk of overrun time and budgets. One of the main targets of requirement engineering is to develop a requirement document with high quality. So, we proposed a user interface to collect all vital information about the project directly from the regular user and requirement engineering;After that, the proposal will generate an ontology based on semantic relations and rules. Requirements Engineering tries to keep requirements throughout a project’s life cycle consistent necessities clear, and up to date. This prototype allows mapping requirement scenarios into ontology elements for semantically interrupted. The general points of our prototype are to guarantee the identification requirements and improved nature of the Software Requirements Specification (SRS) by solving incomplete and conflicting information in the requirements specification.

基于Ontology的网络地理服务描述与发现

针对目前Web服务的行业标准中服务描述和发现方法的不足 ,提出了一种基于Ontology的网络地理信息服务描述和发现方法。其核心思想是采用“概念层 应用层”两个层次来描述地理信息服务 ,将服务发布后 ,通过对服务描述中输入输出等参数和用户需求中功能描述的测度来判断服务与用户需求的匹配程度 ,从而进行服务发现。

领域Ontology概念描述体系构建方法探析

通过对Ontology构建研究存在的问题,以及与传统信息组织方式之间的关系进行详细分析的基础上,吸取笔者在具体构建过程中的经验教训,对构建领域Ontology概念描述体系的有效方法与途径进行了深入探讨,并在提出解决方案的同时,着重探讨了已有公认领域知识以及领域专家有效参与这两个快速构建领域Ontology概念描述体系必备条件的实现途径与方法。

基于Ontology改进的N-Gram文本分类模型研究

文本自动分类技术为Internet上日益严重的“信息过载”问题提供了一种强有力的解决方法。面向中文文本分类领域,将ontology引入到N-Gram统计文本模型中,提出了一种基于“领域概念+有效词链”的多索引策略和相应的权重计算、参数平滑方法。通过在真实数据集上实验表明:应用领域本体的N-Gram中文文本分类模型不仅降低了索引项的数目,而且提高了文本分类的准确率。

Efficient semantic web service matching using common ontology

To solve the bottleneck problem in centralized service discovery methods,a novel architecture based on domain ontology for semantic service discovery is proposed.This distributed architecture can adjust the domain partition and allocate system resources automatically.The characteristics of this mechanism are analyzed,including scalability,self-organization and adaptability.In this mechanism,semantic web service discovery is separated into two parts.First,under balance tree topology,registry proxy can rapidly forward requests to the objective registry center,and avoid the bottleneck problem.Secondly,a semantic distance based service matching algorithm is proposed to promote the effect of service searching.The results of simulation experiments show that the proposed mechanism can serve as a scalable solution for semantic web service publication and discovery.And the improved matching algorithm has higher recall and precision than other algorithms.

领域Ontology的自动丰富——基于ADL地名表的实例研究

本文以一个地理特征词表(Feature Type Thesaurus,FTT)为研究实例,提出了一种对领域Ontology进行自动丰富的方法。FTT描述了200多种地理特征类型,依照等级结构组织,用于标引和组织美国亚历山大数字图书馆地名表(ADL Gazetteer)中的6百万个地名。为了对FTT进行自动丰富,(1)首先从地名中抽取和发现有检索价值的、表示地理特征类型的通用词;(2)根据它们和标引主题词间的同现关系,在相同词族词汇的聚类过程中,确定与之相对应的主题词,进而将提取出的通用词定位到FTT的等级结构中。充分利用已经存在的大量标引语料,实现通用词的定位分析是核心内容,并且实验结果证明有效性达到82.7%。这项研究的实质是从Ontology标引的语料库中自动提取领域知识和标引知识,达到对Ontology的自动丰富。这一方法可以应用到类似的语料库和知识库上,实现新术语的发现、Ontology自丰富及其互操作。

利用ontology实现的多库知识获取方法

在ontology研究的基础上,提出了一种基于ontology的多库知识获取(OBMDKA)方法。考虑到不同用户有不同的表述习惯,引入自然语言理解(NLU)子系统和用户ontology,在正确理解用户语义的前提下方便用户查询。同一知识的表示形式是多种多样的,按不同的表示形式将其分别存放在不同的库中。利用领域ontology对待查找知识进行分类,使查找更加准确全面。

An Ontology-Based Information Retrieval Model for Vegetables E-Commerce

With the rapid increment of the information on the web, traditional information retrieval based on the keywords is far from user＇s satisfaction in recall and precision. In order to improve the recall ratio and the precision radio of IR engine in the vegetables e-commerce, an information retrieval model based on the vegetables e-commerce ontology is presented in this paper, vegetables e-commerce ontology was constructed by gathering and the analyzing vegetables e-commerce domain information on the web. The vegetables e-commerce ontology is composed of some kinds of vegetable classes and hierarchy relationship of vegetables classes. In the process of information retrieval, domain ontology helps to index information and information inference. An ontology-based information retrieval model is implemented, and which has more functions than the keyword-based web information retrieval engines. The experiment results show that the recall ratio and the precision ratio of ontology-based information retrieval model are higher than that of the information retrieval engine based on keyword at a certain extent.

Ontology自动创建中实例学习的研究

Ontology近年来受到信息科学领域的广泛关注,其重要性已在许多方面表现出来并得到广泛认同。自动创建领域Ontology可以克服手工方法的不足,成为当前的研究热点之一;实例(Instance)是Ontology的重要组成元素,从领域文档集中学习实例是自动创建领域Ontology的关键之一。研制的一个领域Ontology的自动生成系统(OntoAGS)能够通过领域文档集自动地创建该领域的Ontology,OntoAGS系统的实例学习是基于模式匹配的算法。实验表明,与当前较流行的Ontology半自动生成系统text-to-onto相比,OntoAGS通常能学习出更多实例,且准确率较高。

基于Ontology的电子税务集成方法

提出了一种基于Ontology的电子税务集成方法 ,旨在解决语义异构问题 .首先建立了电子税务数据概念模型 ,然后给出了领域本体的定义和相关运算规则 ,并以此为基础 ,重点讨论了领域内系统集成和领域外系统集成的方法 。

Review on the Work of Agriculture Ontology Research Group

This paper introduces efforts and achievements of Agriculture Ontology Service Research Group of Agricultural Information Institute of Chinese Academy of Agriculture Sciences in last 10 years. It summarizes the research on ontology construction methodology, ontology management system, ontology application and etc.