Web本体语言的逻辑语义分析的研究

分析了OWL的3个子语言,特别是OWLDL的DL逻辑语义。OWLDL和OWLLite分别与SH系的SHOIN(D)和SHIF(D)对应。通过定义本体的传递概念匹配模式,给出了基于该模式的降水量管理知识模型作为DL推理示例。该示例表明深入分析研究OWL的DL语义对增强基于OWL推理能力的应用具有现实意义。

Description logics for fuzzy ontologies on semantic web

To enable representation and reasoning for fuzzy ontologies with expressive fuzzy knowledge on the semantic web, a new fuzzy extension of description logics called the fuzzy description logics with comparison expressions （FCDLs） is presented. The syntax and semantics of FCDLs are formally defined, and the forms of axioms and assertions in FCDLs knowledge bases are specified. FCDLs combine both fuzzy concepts from the fuzzy description logics （FDLs） and cut concepts from the extended fuzzy description logics （EFDLs） in the same theory. Furthermore, cut concepts are extended into comparison cut concepts in FCDLs to represent comparison expressions between fuzzy membership degrees, which are often used in practice but not supported by the other fuzzy extensions of description logics. FCDLs have more expressive power than FDLs and EFDLs, and are able to represent expressive fuzzy knowledge and to perform reasoning tasks based on them. Therefore, FCDLs can enable representation and reasoning for fuzzy ontologies with expressive fuzzy knowledge on the semantic web.

Web services selection based on semantic similarity

Services discovery based on syntactic matching cannot adapt to the open and dynamic environment of the web. To select the proper one from the web services candidate set provided by syntactic matching, a service selection method based on semantic similarity is proposed. First, this method defines a web services ontology including QoS and context as semantic supporting, which also provides a set of terms to describe the interfaces of web services. Secondly, the similarity degree of two web services is evaluated by computing the semantic distances of those terms used to describe interfaces. Compared with existing methods, interfaces of web services can be interpreted under ontology, because it provides a formal and semantic specification of conceptualization. Meanwhile, efficiency and accuracy of services selection are improved.

Task-oriented web service discovery algorithm using semantic similarity for adaptive service composition

In order to achieve adaptive and efficient service composition, a task-oriented algorithm for discovering services is proposed. The traditional process of service composition is divided into semantic discovery and functional matching and makes tasks be operation objects. Semantic similarity is used to discover services matching a specific task and then generate a corresponding task-oriented web service composition （TWC） graph. Moreover, an algorithm for the new service is designed to update the TWC. The approach is applied to the composition model, in which the TWC is searched to obtain an optimal path and the final service composition is output. Also, the model can implement realtime updating with changing environments. Experimental results demonstrate the feasibility and effectiveness of the algorithm and indicate that the maximum searching radius can be set to 2 to achieve an equilibrium point of quality and quantity.

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.

Semantic web-based networked manufacturing knowledge retrieval system

To deal with a lack of semantic interoperability of traditional knowledge retrieval approaches, a semantic-based networked manufacturing （NM） knowledge retrieval architecture is proposed, which offers a series of tools for supporting the sharing of knowledge and promoting NM collaboration. A 5-tuple based semantic information retrieval model is proposed, which includes the interoperation on the semantic layer, and a test process is given for this model. The recall ratio and the precision ratio of manufacturing knowledge retrieval are proved to be greatly improved by evaluation. Thus, a practical and reliable approach based on the semantic web is provided for solving the correlated concrete problems in regional networked manufacturing.

Ontology mapping approach using web search engine

A new mapping approach for automated ontology mapping using web search engines （such as Google） is presented. Based on lexico-syntactic patterns, the hyponymy relationships between ontology concepts can be obtained from the web by search engines and an initial candidate mapping set consisting of ontology concept pairs is generated. According to the concept hierarchies of ontologies, a set of production rules is proposed to delete the concept pairs inconsistent with the ontology semantics from the initial candidate mapping set and add the concept pairs consistent with the ontology semantics to it. Finally, ontology mappings are chosen from the candidate mapping set automatically with a mapping select rule which is based on mutual information. Experimental results show that the F-measure can reach 75% to 100% and it can effectively accomplish the mapping between ontologies.

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.

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.

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.

Design and implementation of semantic search engine Smartch

To integrate reasoning and text retrieval, the architecture of a semantic search engine which includes several kinds of queries is proposed, and the semantic search engine Smartch is designed and implemented. Based on a logical reasoning process and a graphic user-defined process, Smartch provides four kinds of search services. They are basic search, concept search, graphic user-defined query and association relationship search. The experimental results show that compared with the traditional search engine, the recall and precision of Smartch are improved. Graphic user-defined queries can accurately locate the information of user needs. Association relationship search can find complicated relationships between concepts. Smartch can perform some intelligent functions based on ontology inference.

Approximate querying between heterogeneous ontologies based on association matrix

An approximate approach of querying between heterogeneous ontology-basedinformation systems based on an association matrix is proposed. First, the association matrix isdefined to describe relations between concepts in two ontologies. Then, a methodof rewriting queriesbased on the association matrix is presented to solve the ontology heterogeneity problem. Itrewrites the queries in one ontology to approximate queries in another ontology based on thesubsumption relations between concepts. The method also uses vectors to represent queries, and thencomputes the vectors with the association matrix; the disjoint relations between concepts can beconsidered by the results. It can get better approximations than the methods currently in use, whichdonot consider disjoint relations. The method can be processed by machines automatically. It issimple to implement and expected to run quite fast.

Context-driven reconciliation in ontology integration

In order to solve the semantic irreconcilable problems caused by contextual differences during the process of ontology integration, a context-driven reconciliation mechanism is proposed. The mechanism is based on the previous work about a context-based formalism-Context-SHOIQ （D ＋ ） DL, which is used for explicitly representing context of ontology by adopting the description logic and the category theory. The formalism is extended by adding four migration rules （InclusionRule, SelectionRule, PreferenceRule, and MappingRule）, that are used to specify what should be imported into the IntegrativeContext, and three related contextual integration operations of increasing interoperability （import, partial reconciliation, and full reconciliation）. While not exhaustive, the mechanism is sufficient for solving the five types of semantic irreconcilable problems that are discussed, and favors integration of ontologies from one context to another.

Semantics-Based Compliance An a lys is o f N e two rk S e cu rity Policy Hie ra rch ie s

Network security policy and the automated refinement of its hierarchies aims to simplify the administration of security services in complex network environments. The semantic gap between the policy hierarchies reflects the validity of the policy hierarchies yielded by the automated policy refinement process. However, little attention has been paid to the evaluation of the compliance between the derived lower level policy and the higher level policy. We present an ontology based on Ontology Web Language （OWL） to describe the semantics of security policy and their implementation. We also propose a method of estimating the semantic similarity between a given

An Edge-Based Approach for Semantic Matchmaking of Service Capabilities

Semantic Web Services is an emerging technology that promises to enable dynamic, execution-time discovery, composition, and invocation of Web Services. Semantic matchmaking plays a vital role in the automated and dynamic discovery process of Semantic Web Services and consists in measuring the semantic distance between a requested service and an advertised one. In this paper, an innovative approach to effectively compute the semantic distance between Ontology Web Language for Services （OWL-S） annotated services is proposed. First, an edge-based method for measuring the semantic distance between Web Ontology Language （OWL） concepts is presented. Then, a comparison of the proposed measure and the one presented in a recent related work is made in order to show that our method is more efficient and fine-grained. Finally, some equations to compute semantic matchmaking of service capabilities, which are expressed in terms of inputs and outputs, are presented.

Data Migration for Ontology Evolution

Ontology is the conceptual backbone that provides meaning to data on the semantic web. However, ontology is not a static resource and may evolve over time, which often leaves the meaning of data in an undefined or inconsistent state. It is thus very important to have a method to preserve the data and its meaning when ontology changes. This paper proposed a general method that solves the problem using data migration. It analyzed some of the issues in the method including separation of ontology and data, migration specification, migration result and migration algorithm. The paper also instantiates the general mothod in RDF(S) as an example. The RDF(S) example itself is a simple but complete method for migrating RDF data when RDFS ontology changes.

Fuzzy Recognition Method for Fish Ontology Retrieving

This paper presents a new method based on ontology formarion and fuzzy recognition of digital pictures. Ontology creation and doormat indexing are well-kown bottlenecks for integrating semantic services and for the Semantic Web, and thus the new method will be able to make automatic creation of the fish geometric ontology and automatic indexing to existing Semantic Web. Fuzzy set and fuzzy recognition are used to decide wheter a new fish picture belongs to an existing training set, here with the carp as an example. Training ing samples are used to set up fuzzy set and membership functions. The existing way of fish ontology formation can be integrated with the new method and the existing work for fish web can be used.

A novel approach for agent ontology and its application in question answering

The information integration method of semantic web based on agent ontology(SWAO method) was put forward aiming at the problems in current network environment,which integrates,analyzes and processes enormous web information and extracts answers on the basis of semantics. With SWAO method as the clue,the following technologies were studied:the method of concept extraction based on semantic term mining,agent ontology construction method on account of multi-points and the answer extraction in view of semantic inference. Meanwhile,the structural model of the question answering system applying ontology was presented,which adopts OWL language to describe domain knowledge from where QA system infers and extracts answers by Jena inference engine. In the system testing,the precision rate reaches 86%,and the recalling rate is 93%. The experimental results prove that it is feasible to use the method to develop a question answering system,which is valuable for further study in more depth.

An XPath-based OWL storage model for effective ontology management in Semantic Web environment

With the rapid growth of the Web, the volume of information on the Web is increasing exponentially. However, information on the current Web is only understandable to humans, and this makes precise information retrieval difficult. To solve this problem, the Semantic Web was proposed. We must use ontology languages that can assign data the semantics for realizing the Semantic Web. One of the representative ontology languages is the Web ontology language OWL, adopted as a recommen-dation by the World-Wide Web Consortium (W3C). OWL includes hierarchical structural information between classes or prop-erties. Therefore, an efficient OWL storage model that considers a hierarchical structure for effective information retrieval on the Semantic Web is required. In this paper we suggest an XPath-based OWL storage (XPOS) model, which includes hierarchical information between classes or properties in XPath form, and enables intuitive and effective information retrieval. Also, we show the comparative evaluation results for the performance of the XPOS model, Sesame, and the XML file system-based storage (XFSS) model, in terms of query processing and ontology updating.