Ontology的类型及汉语词网的Ontology结构

Ontology在不同领域有不同的理解,本文在阐述哲学和人工智能领域Ontology差异的基础上,揭示了它们间的联系,建构了哲学、技术和语言三足鼎立的Ontology系统,着重论述了语言Ontology及其结构。并认为Ontology是一种思维方式和方法,随着其应用领域的延伸,还会有新的不同类型的Ontology产生。

General ontology learning framework

In order to reduce the costs of the ontology construction, a general ontology learning framework （GOLF） is developed. The key technologies of the GOLF including domain concepts extraction and semantic relationships between concepts and taxonomy automatic construction are proposed. At the same time ontology evaluation methods are also discussed. The experimental results show that this method produces better performance and it is applicable across different domains. By integrating several machine learning algorithms, this method suffers less ambiguity and can identify domain concepts and relations more accurately. By using generalized corpus WordNet and HowNet, this method is applicable across different domains. In addition, by obtaining source documents from the web on demand, the GOLF can produce up-to-date ontologies.

Process Philosophical Adventures of Applied Ontology

The paper is devoted to the new sphere of applied process ontology. It first makes a short review of the recent investigations in that area. Then it stresses on the importance of applied process ontology. Next the main methodological approaches of applied process ontology are considered： the ＂top down＂ and ＂bottom up＂ approaches. It is argued about the necessity and fruitfulness to combine both ＂top down＂ and ＂bottom up＂ approaches, and not to rely on one of them only. An example is given of the important role of process ontology as general methodological framework for the building up of regional formal ontology. Finally, the idea of variable ontological categories is stressed on and argued for its fruitfulness.

Ontology Engineering and Knowledge Services for Agriculture Domain

This paper presents a knowledge service system for the domain of agriculture. Three key issues for providing knowledge services are how to improve the access of unstructured and scattered information for the non-specialist users, how to provide adequate information to knowledge workers and how to provide the information requiring highly focused and related information. Cyber-Brain has been designed as a platform that combines approaches based on knowledge engineering and language engineering to gather knowledge from various sources and to provide the effective knowledge service. Based on specially designed ontology for practical service scenarios, it can aggregate knowledge from Internet, digital archives, expert, and other resources for providing one-stop-shop knowledge services. The domain specific and task oriented ontology also enables advanced search and allows the system ensures that knowledge service could improve the user benefit. Users are presented with the necessary information closely related to their information need and thus of potential high interest. This paper presents several service scenarios for different end-users and reviews ontology engineering and its life cycle for supporting AOS （Agricultural Ontology Services） Vocbench which is the heart of knowledge services in agriculture domain.

基于Ontology的大规模知识库构建技术分析

基于Ontology的大规模知识库系统是语义内容应用的基础.文章介绍了四个有代表性的基于Ontology的大规模知识库系统,分别分析了系统的关键技术、特点和性能,并对它们的性能进行了对比分析,最后分析了当前系统的局限、挑战和趋势,以期对国内数字图书馆知识库建设有所帮助.该文为2008年第9期本期话题'知识抽取'的文章之一.

Using ontology and rules to retrieve the semantics of disaster remote sensing data

Remote sensing data plays an important role in natural disaster management.However,with the increase of the variety and quantity of remote sensors,the problem of“knowledge barriers”arises when data users in disaster field retrieve remote sensing data.To improve this problem,this paper proposes an ontology and rule based retrieval(ORR)method to retrieve disaster remote sensing data,and this method introduces ontology technology to express earthquake disaster and remote sensing knowledge,on this basis,and realizes the task suitability reasoning of earthquake disaster remote sensing data,mining the semantic relationship between remote sensing metadata and disasters.The prototype system is built according to the ORR method,which is compared with the traditional method,using the ORR method to retrieve disaster remote sensing data can reduce the knowledge requirements of data users in the retrieval process and improve data retrieval efficiency.

Web integration based on classification ontology

In order to eliminate semantic heterogeneity and implement semantic combination in web information integration, the classification ontology is introduced into web information integration. It constructs a standard classification ontology based on web-glossary by extracting classified structures of websites and building mappings between them in order to get unified views. Mapping is defined by calculating concept subordinate matching degrees, concept associate matching degrees and concept dominate matching degrees. A web information integration system is realized, which can effectively solve the problem of classification semantic heterogeneity and implement the integration of web information source and the personal configuration of users.

Ontology based approach of semantic information integration

In order to solve the problem of semantic heterogeneity in information integration, an ontology based semantic information integration （OSII） model and its logical framework are proposed. The OSII adopts the hybrid ontology approach and uses OWL （web ontology language） as the ontology language. It obtains unified views from multiple sources by building mappings between local ontologies and the global ontology. A tree- based multi-strategy ontology mapping algorithm is proposed. The algorithm is achieved by the following four steps： pre-processing, name mapping, subtree mapping and remedy mapping. The advantages of this algorithm are： mapping in the compatible datatype categories and using heuristic rules can improve mapping efficiency; both linguistic and structural similarity are used to improve the accuracy of the similarity calculation; an iterative remedy is adopted to obtain correct and complete mappings. A challenging example is used to illustrate the validity of the algorithm. The OSII is realized to effectively solve the problem of semantic heterogeneity in information integration and to implement interoperability of multiple information sources.

Ontology mapping based on hidden Markov model

The existing ontology mapping methods mainly consider the structure of the ontology and the mapping precision is lower to some extent. According to statistical theory, a method which is based on the hidden Markov model is presented to establish ontology mapping. This method considers concepts as models, and attributes, relations, hierarchies, siblings and rules of the concepts as the states of the HMM, respectively. The models corresponding to the concepts are built by virtue of learning many training instances. On the basis of the best state sequence that is decided by the Viterbi algorithm and corresponding to the instance, mapping between the concepts can be established by maximum likelihood estimation. Experimental results show that this method can improve the precision of heterogeneous ontology mapping effectively.

基于奇异值分解的中文Ontology自动学习技术

语义Web是一个美好的构想，Ontology在语义Web中起着举足轻重的作用，它不仅能为人类用户而且能为软件agent提供从语法层次到语义层次上的互操作性。目前Web上主要是各种布局的HTML文档，未来的语义Web页面将是各种领域Ontology的实例以及到其它实例上的链接，因此语义Web的成功强烈依赖于Ontology的增殖，方便快捷地构造各领域Ontologies是实现语义Web的关键。该文提出一种基于奇异值分解的中文Ontology自动学习技术，这种技术的特点是其简易性以及准确的数学理论基础。

也谈关于Ontology的翻译

如何翻译和理解Ontology这一重要概念 ,对研究西方哲学的存在理论关系极大 ,对它的理解又最终被归结为对tobe的理解。国内西方哲学界对此的看法历来有异 ,近年又有研究者认为以“是”来翻译和理解tobe最为准确。本文根据当代著名语言学、哲学史专家美国学者卡恩的研究成果 ,讨论了tobe本来具有的多种用法、多重涵义。认为它的一种主要和基本的用法 ,是作系动词用 ,表示“是”的意义 ;即使在作为系动词用时 ,它也可以表示“是者”、“存在” ,包含“是者”、“存在”的意义 ;它究竟表示“是”还是“存在”或别的意义 ,要看使用它的不同时代、不同语境和不同哲学家 ;而tobe所含有的“存在”的意义 ,在不同的形而上学理论中 ,又有差异 ,有的指本体意义的“存在” ,有的指实存意义上的“存在” ,有的则指自身显现意义上的“存在”。因此 ,对Ontology的翻译和理解 ,也应该视不同情形而定。

New automated ontology mapping algorithm

A new algorithm for automated ontology mapping based on linguistic similarity and structure similarity is presented. First, the concept of WordNet is turned into a vector, then the similarity of two entities is calculated according to the cosine of the angle between the corresponding vectors. Secondly, based on the linguistic similarity, a weighted function and a sigmoid function can be used to combine the linguistic similarity and structure similarity to compute the similarity of an ontology. Experimental results show that the matching ratio can reach 63% to 70% and it can effectively accomplish the mapping between ontologies.

Rules-based object-relational databases ontology construction

To solve the problems of shaving and reusing information in the information system, a rules-based ontology constructing approach from object-relational databases is proposed. A 3-tuple ontology constructing model is proposed first. Then, four types of ontology constructing rules including class, property, property characteristics, and property restrictions ave formalized according to the model. Experiment results described in Web ontology language prove that our proposed approach is feasible for applying in the semantic objects project of semantic computing laboratory in UC Irvine. Our approach reduces about twenty percent constructing time compared with the ontology construction from relational databases.

Design of ontology mapping framework and improvement of similarity computation

Ontology heterogeneity is the primary obstacle for interoperation of ontologies. Ontology mapping is the best way to solve this problem. The key of ontology mapping is the similarity computation. At present, the method of similarity computation is imperfect. And the computation quantity is high. To solve these problems, an ontology-mapping framework with a kind of hybrid architecture is put forward, with an improvement in the method of similarity computation. Different areas have different local ontologies. Two ontologies are taken as examples, to explain the specific mapping framework and improved method of similarity computation. These two ontologies are about classes and teachers in a university. The experimental results show that using this framework and improved method can increase the accuracy of computation to a certain extent. Otherwise, the quantity of computation can be decreased.

Approach for knowledge sharing based on ontology context immigration

In order to better achieve knowledge sharing based on distributed ontologies, an approach based on ontology context immigration （OCI）is proposed. Compared with traditional approaches such as ontology integration and mapping, the proposed approach can reduce the implementation complexity. This approach can be mainly divided into three phases： ontology context determination for a given term, ontology semantic similarity computation between ontology terms, and ontology context immigration. As for a local semantic term based on distributed ontologies, an appropriate ontology context of the term is determined and extracted from a local ontology most associated with the term by using semantic similarity computation. Then, the ontology context is dynamically immigrated to the source ontology for enriching semantic information related to the term. A system called distributed knowledge sharing system（DKSS） is developed to illustrate this approach. The system adopts multi-agent technology for better communication and coordination between different ontology information sources. The experimental results show that it is efficient for distributed ontology knowledge sharing. The proposed approach does not require the support of a global ontology or the maintenance of complex ontology mapping relations, and thus it has better maintainability and scalability.

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.

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.

组织数字信息资源的元数据方法和Ontology方法

元数据方法和ontology方法有不同的渊源与应用领域。随着信息技术的发展和元数据、ontology 研究的深入,元数据与ontology相互借鉴、相互融合的特征日益显现。元数据的ontology模型便是这种特征的例证与具体体现。

Ontology研究综述

Ontology是描述概念及概念之间关系的概念模型 ,通过概念之间的关系来描述概念的语义。作为一种有效表现概念层次结构和语义的模型 ,Ontology被广泛地应用到计算机科学的众多领域。本文作者对目前Ontology的研究与应用现状进行了综述性地介绍 ,从Ontology的定义、Ontol ogy理论研究、Ontology在信息系统中的应用以及在语义Web中的地位等方面加以了系统阐述。

Towards a Formalized Ontology-Based Requirements Model

The goal of this paper is to take a further step towards an ontological approach for representing requirements information. The motivation for ontologies was discussed. The definitions of ontology and requirements ontology were given. Then, it presented a collection of informal terms, including four subject areas. It also discussed the formalization process of ontology. The underlying meta-ontology was determined, and the formalized requirements ontology was analyzed. This formal ontology is built to serve as a basis for requirements model. Finally, the implementation of software system was given.