The Semantic Web – ASWC 2006

If you visit my Web page, which is not much different than most other people’s in many ways, you would find many fields which are highlighted as links to other pages. In the list of my students you can find links to their pages, in the links of my papers you can find downloadable files or links to various digital libraries, and in the lists of my classes you can find links both to the Web resources I used in my classes and to University pages that describe when the classes were given, what the prerequisites were, etc. In short, a great deal of the information “on my page” is not actually on my page at all, it is provided by the linking mechanisms of the Web. It is, in fact, exactly this network effect in which I can gain advantage by linking to information created by other people, rather than recreating it myself, that makes the Web so powerful.

Semantics shows diversity in real world, document world, mental abstraction world and machine world. Transformation between semantics pursues the uniformity in the diversity. The Resource Space Model (RSM) is a semantic data model for organizing resources based on the classification semantics that human often use in understanding the real world. The design of a resource space relies on knowledge about domain and the RSM. Automatically creating resource space can relieve such reliance in RSM applications. This paper proposes an approach to automatically transform Web Ontology Language description into resource space. The normal forms of the generated resource space are investigated to ensure its normalization characteristic. The Dunhuang culture resource space is used to illustrate the approach.

In this short paper, we examine current Semantic Web application and we highlight what we see as a shift away from first generation Semantic Web applications, towards a new generation of applications, designed to exploit the large amounts of heterogeneous semantic markup, which are increasingly becoming available. Our analysis aims both to highlight the main features that can be used to compare and contrast current Semantic Web applications, as well as providing an initial blueprint for characterizing the nature of Semantic Web applications. Indeed, our ultimate goal is to specify a number of criteria, which Semantic Web applications ought to satisfy, if we want to move away from conventional semantic systems and develop a

new generation of Semantic Web applications

, which can succeed in applying semantic technology to the challenging context provided by the World-Wide-Web.

With the current growing interest in the Semantic Web, the demand for ontological data has been on the verge of emergency. Currently many structured and semi-structured documents have been applied for ontology learning and annotation. However, most of the electronic documents on the web are plain-text, and these texts are still not well utilized for the Semantic Web. In this paper, we propose a novel method to automatically extract topic terms to generate a concept hierarchy from the data of Chinese Bulletin Board System (BBS), which is a collection of plain-text. In addition, our work provides the text source associated with the extracted concept as well, which could be a perfect fit for the semantic search application that makes a fusion of both formal and implicit semantics. The experimental results indicate that our method is effective and the extracted concept hierarchy is meaningful.

This paper describes an approach to automatically annotate documents for the Euro-Mediterranean Water Information System. This approach uses the citation links and co-citation measure in order to refine annotations extracted from an indexation method. An experiment of this approach with the CiteSeer database is presented and discussed.

This paper addresses the issue of semantic annotation using horizontal and vertical contexts. Semantic annotation is a task of annotating web pages with ontological information. As information on a web page is usually two-dimensionally laid out, previous semantic annotation methods that view a web page as an ‘object’ sequence have limitations. In this paper, to better incorporate the two-dimensional contexts, semantic annotation is formalized as a problem of block detection and text annotation. Block detection is aimed at detecting the text block by making use of context in one dimension and text annotation is aimed at detecting the ‘targeted instance’ in the identified blocks using the other dimensional context. A two-stage method for semantic annotation using machine learning has been proposed. Experimental results indicate that the proposed method can significantly outperform the baseline method as well as the sequence-based method for semantic annotation.

Since its birth in 1995, Wiki has become more and more popular. This paper presents a Semantic Wiki, a Wiki extended to include the ideas of Semantic Web. The proposed Semantic Wiki uses a simple Wiki syntax to write labeled links which represent RDF triples. By enabling the writing of labeled links, Semantic Wiki may provide an easy-to-use and flexible environment for an integrated management of content and metadata, so that Semantic Wiki may be used as a lightweight knowledge management system.

Ontology matching is a crucial task of enabling interoperation between Web applications using different but related ontologies. Due to the size and the monolithic nature, large-scale ontologies regarding real world domains cause a new challenge to current ontology matching techniques. In this paper, we propose a method for partition-based block matching that is practically applicable to large class hierarchies, which are one of the most common kinds of large-scale ontologies. Based on both structural affinities and linguistic similarities, two large class hierarchies are partitioned into small blocks respectively, and then blocks from different hierarchies are matched by combining the two kinds of relatedness found via predefined anchors as well as virtual documents between them. Preliminary experiments demonstrate that the partition-based block matching method performs well on our test cases derived from Web directory structures.

With the development of semantic web technologies, large and complex ontologies are constructed and applied to many practical applications. In order for users to quickly understand and acquire information from these huge information “oceans”, we propose a novel ontology visualization approach accompanied by “anatomies” of classes and properties. With the holistic “imaging”, users can both quickly locate the interesting “hot” classes or properties and understand the evolution of the ontology; with the anatomies, they can acquire more detailed information of classes or properties that is arduous to collect by browsing and navigation. Specifically, we produce the ontology’s holistic “imaging” which contains a semantic layout on classes and distributions of instances. Additionally, the evolution of the ontology is illustrated by the changes on the “imaging”. Furthermore, detailed anatomies of classes and properties, which are enhanced by techniques in database field (e.g. data mining), are ready for users.

Ontology matching has played a great role in many well-known applications. It can identify the elements corresponding to each other. At present, with the rapid development of ontology applications, domain ontologies became very large in scale. Solving large scale ontology matching problems is beyond the reach of the existing matching methods. To improve this situation a modularization-based approach (called MOM) was proposed in this paper. It tries to decompose a large matching problem into several smaller ones and use a method to reduce the complexity dramatically. Several large and complex ontologies have been chosen and tested to verify this approach. The results show that the MOM method can significantly reduce the time cost while keeping the high matching accuracy.

In current Semantic Web community, some researches have been done on ranking ontologies, while very little is paid to ranking vocabularies within ontology. However, finding important vocabularies within a given ontology will bring benefits to ontology indexing, ontology understanding and even ranking vocabularies from a global view. In this paper, Vocabulary Dependency Graph (VDG) is proposed to model the dependencies among vocabularies within an ontology, and Textual Score of Vocabulary (TSV) is established based on the idea of virtual documents. And then a Double Focused PageRank algorithm is applied on VDG and TSV to rank vocabulary within ontology. Primary experiments demonstrate that our approach turns out to be useful in finding important vocabularies within ontology.

This paper firstly utilizes the ontology such as WordNet to build the semantic structures of text documents, and then enhance the semantic similarity among them. Because the correlations between documents make them lie on or close to a smooth low-dimensional manifold so that documents can be well characterized by a manifold within the space of documents, we calculate the similarity between any two semantically structured documents with respect to the intrinsic global manifold structure. This idea has been validated in the conducted text categorization experiments on patent documents.

We present a set of primitive restructuring operators that, when combined, are sufficiently powerful to convert an XML document under a source schema into an XML document under an arbitrary target schema. We initially define the operators at the schema level, and then show how each operator induces a corresponding transformation on any XML document under the schema. Finally, we note that our operators can be implemented in a high level language such as XQuery, and thus our approach can be used as the basis for automating the conversion of one XML document to another XML document.

As the need for personalized services sharply increases caused by the booming of Internet, Web-based data-mining is becoming a valuable sources of thoughts and theory to satisfy the personalized system function. The characters of personalized data-mining is reviewed and discussed in the beginning, and then an innovative algorithm (FP-Tree time – validity algorithm ) of Web pageviews, based on personalization, is raised. More authentic information can be efficiently got by adding time-validity coefficient to FTT-Tree storage structure to implement increment mining.

Todays WWW consists of more than just information. The WWW provides a large number of services, which often require identification of it’s users. This has lead to the fact that today users have to maintain a large number of different credentials for different websites – distributed or shared identification system are not widely deployed. Furthermore current authorisation systems requires strict centralisation of the authorisation procedure – users themselves are usually not enabled to authorise their trusted friends to access services, although often this would be beneficial for services and businesses on the Web.

In this article we present D-FOAF, a distributed identity management system which deploys social networks. We show how information inherent in social networks can be utilised to provide community driven access rights delegation and we analyse algorithms for managing distributed identity, authorisation and access rights checking. Finally we show how the social networking information can be protected in a distributed environment.

A social networking service can become the basis for the information infrastructure of the future. For that purpose, it is important to extract social networks that reflect actual social networks which users have already had. Providing a simple means for users to register their social relations is also important. We propose a method that combines various approaches to extract social networks. Especially, three kinds of networks are extracted: user-registered

Know-link

networks; Web-mined

Web-link

networks; and face-to-face

Touch-link

networks. This paper describes the combination of social network extraction for an event-participant community. Analyses on the extracted social networks are also presented.

This paper analyze the influence of the relations among blogs on users’ browsing behavior assuming that users’ activities can be predict by the relations on the blog network. We define the measure for two-hop relations as a factor to influence activities, and check the correlation between them or with users’ behavior by using blog data including visiting behavior. Attempting to determine the relations on which users read the blogs with interest as a helpful information for page recommendation, we conduct the experiments with a machine learning. As a result, even though the performance is not very high, we get the effective factors for prediction.

Due to the proliferation of information exchange via Internet, users suffer from information overload. For this reason, RSS is now widely adopted to deliver latest information to users without human intervention. It is also used to deliver customized data using extension modules. However an inter-operability issue among RSS applications using different extension modules has been raised because the processing of extension module has to be performed in the source code level of RSS applications. To resolve this interoperability issue, we propose a new RSS framework, UniRSS, which can support extension modules via a unified interface. UniRSS suggests an architecture composed of a pair of describing schema and a delegation code model to support any kind of extension modules in the code level. It supports both RSS 1.0 and RSS 2.0, and it also provides intelligent syndication using reasoning code insertion for RSS 1.0.

Today, the formulation, specification, and verification of adequate data protection policies in open distributed environment appear as the main challenge to address concerning authorization. Role-based access control models have attracted considerable research interest in recent years due to their innate ability to model organizational structure and their potential to reduce administrative overheads. This paper proposes ontology specification to describe Role-based Access Control model and extend it with a general context expression. Based on these definitions, the specification for interoperation in distributed environment is introduced. The works include a definition of ontology to describe the concepts and a declaration of rules to explicit the relationship between concepts. The ontology based approach can express security policy with semantic information and provide a machine interpretation for descriptions of policy in open distributed environment.

Business process collaboration is one of the most significant factors driving today’s global business development. Researches and applications such as business process modeling, workflow interoperability, web service and ambient intelligence have been involved in this area. However, a holistic understanding is missing. To clarify the requirements and build a research foundation for business process collaboration, a conceptual model is provided in this paper. Then the state of the art and the future trend of business process modeling and process interoperability are reviewed based on this model. Furthermore, inspired by the novel semantic web technologies, a semantic agent based framework to facilitate business process collaboration is given.

Ontologies are expected in various areas as promising tools to improve communication among people and to achieve interoperability among systems. For communications between different business domains, building an ontology through integrating existing ontologies is more efficient way than building the ontology without them. However, integration of ontologies is very struggling work since languages, domains, and structures of ontologies are different from each other. In this paper, we suggest an Ontology Architecture which solves this problem by providing a systematic framework to classify ontologies from three kinds of viewpoints: language, domain range, constructs. The Ontology Architecture consists of three axes according to the three viewpoints: Ontology Meta Layering axis, Semantic Domain Layering axis, and Ontology Constructs Layering axis. Because three axes in the Ontology Architecture are designed to improve the syntactic and semantic interoperability among ontologies, the integration of ontologies can be readily achieved.

This paper describes a novel approach of detecting misalignment at the time of aligning two different ontologies, and of eliminating the misalignments. Our objective is to reduce limitation of a specific technique of ontology alignment. Two aligned sets extracted by different alignment techniques from the same pair of ontology, are fed to the misalignment detection and elimination process to produce better alignments. Our experiments demonstrate that our method, taking advantage of misalignment detection and elimination, shows a good recall and precision.

To overcome the challenges of EII (Enterprise Information integration), we propose SGII which is the first system undertaking research at the intersection of semantic grid and P2P data integration, exploiting their strengths in a common framework, and expanding their applicability in the area of EII. We first discuss how the P2P and semantic grid technologies can drive current EII systems to a new decentralized, flexible, scalable system based on a short survey of the state of the art of EII and its current challenges. Then, through a discussion of the fundamental formal architecture in general and its components in particular, we depict the basic integration principles from both P2P and semantic grid perspectives. The key contributions of this paper are a P2P semantic grid service oriented framework for EII, which mainly consists of three semantic grid services (data peer, semantic peer and application peer services); basic integration principles, which is compatible with OGSA-DAI infrastructure and P2P data integration paradigm; and added value over the state of the art of EII.

Application integration is a complex problem that consumes a significant share of the IT budget of many companies and organizations.

CSpaces

aim to improve the current state of the art in system integration by transforming the Semantic Web into a

Semantic Enterprise Service Bus

for application integration and coordination. A use case scenario for integration of heterogeneous project management applications in the construction industry tests the ability of CSpaces to handle integration problems.

Various methods using different measures have been proposed for ontology alignment. Therefore, it is necessary to evaluate the effectiveness of such measures to select better ones for more quality alignment. Current approaches for comparing these measures, are highly dependent on alignment frameworks, which may cause unreal results. In this paper, we propose a framework independent evaluation method, and discuss results of applying it to famous existing string measures.

An application profile specifies a set of terms, drawn from one or more standard namespaces, for annotation of data, and constrains their usage and interpretations in a particular local application. A framework for representing and reasoning with application profiles using the OWL and OWL/XDD languages is proposed. The former is a standard Web ontology language and the latter is a definite-clause-style rule language that employs XML expressions as its underlying data structure. Constraints are defined in terms of rules, which are represented as XDD clauses. Application of the approach to defining an application profile with fine-grained semantic constraints is illustrated. A prototype library metadata validation system has been implemented.

Bridging the gap between OWL and Object-Oriented Programming (OOP) languages is an indispensable condition to enable the Object-Oriented Modeling in Software Engineering by OWL. However it is very difficult in case of static OOP languages like Java and C#. We have developed SWCLOS, which is an OWL processor seamlessly built on top of Common Lisp Object System (CLOS), a dynamic OOP language. SWCLOS allows programmers to develop application domain models by OWL and enables OOP upon the models. In this paper, we explain the semantic gap between OWL and OOP languages, introduce the RDFS and OWL realization at SWCLOS, and discuss the OWL features from OOP perspectives. Finally we demonstrate the OWL-Full level performance in SWCLOS.

Defeasible reasoning is a rule-based approach for efficient reasoning with incomplete and conflicting information. Such reasoning is useful in many Semantic Web applications, like policies, business rules, brokering, bargaining and agent negotiations. Nevertheless, defeasible logic is based on solid mathematical formulations and is, thus, not fully comprehensible by end users, who often need graphical trace and explanation mechanisms for the derived conclusions. Directed graphs can assist in confronting this drawback. They are a powerful and flexible tool of information visualization, offering a convenient and comprehensible way of representing relationships between entities. Their applicability, however, is balanced by the fact that it is difficult to associate data of a variety of types with the nodes and the arcs in the graph. In this paper we try to utilize digraphs in the graphical representation of defeasible rules, by exploiting the expressiveness and comprehensibility they offer, but also trying to leverage their major disadvantage, by defining two distinct node types, for rules and atomic formulas, and four distinct connection types for each rule type in defeasible logic and for superiority relationships. The paper also briefly presents a tool that implements this representation methodology.

pD* semantics extends the ‘if-semantics’ of RDFS to a subset of the OWL vocabulary. It leads to simple entailment rules and relatively low computational complexity for reasoning. In this paper, we propose a forward-chaining reasoning algorithm to support RDFS entailments under the pD* semantics. This algorithm extends the Sesame algorithm to cope with the pD* entailments. In particular, an optimization to the dependent table between entailment rules is presented to eliminate much redundant inferring steps. Finally, some test results are given to illustrate the correctness and performance of this algorithm.

Triple Space Computing (TSC) is a very simple and powerful paradigm that inherits the communication model from Tuple Space Computing and projects it in the context of the Semantic Web. In this paper, we propose Triple Space Computing as a new communication and coordination framework for Semantic Web and Semantic Web Services. We identify the value added by TSC and propose the overall architecture of TSC and the interactions among different components.

One of the big issues facing current content-based image retrieval is how to automatically extract the semantic information from images. In this paper, we propose an efficient method that automatically extracts the semantic information from images by using ontologies and the semantic inference rules. In our method, MPEG-7 visual descriptors are used to extract the visual features of image which are mapped to the semi-concept values. We also introduce the visual and animal ontology which are built to bridge the semantic gap. The visual ontology facilitates the mapping between visual features and semi-concept values, and allows the definition of relationships between the classes describing the visual features. The animal ontology representing the animal taxonomy can be exploited to identify the object in an image. We also propose the semantic inference rules that can be used to automatically extract high-level concepts from images by applying them to the visual and animal ontology. Finally, we discuss the limitations of the proposed method and the future work.

The Web Ontology Language (OWL), which is a Description Logic based ontology language, is widely used to represent formal definitions of vocabularies for domain knowledge, especially in the medical domain. The Semantic Web Rule Language (SWRL), which is a Rule based ontology language, allows users to take advantage of inferencing of new knowledge from existing OWL knowledge base. In this paper, we describe a use case focused on building SWRL rule base on top of the tooth positional ontology represented in OWL so as to assist a dental decision-making on a missing tooth. Then, we discuss limitations of a current SWRL specification, through our experiences on converting dental knowledge into SWRL rules.

This article describes the technical aspects of a particular use of ontologies for visualising maps in a browser window. Geographic data are represented as instances of concepts in an ontology of transportation networks which was designed in close relation to GDF. These data are transformed into SVG, whereas the transformation is specified symbolically as instances of a

transformation ontology

. This approach is extremely flexible and easily extendible to include all kinds of information in the generated maps. This article is an abbreviated version of the research report [5] and focuses only on the technical aspects of the approach.

Government agencies are the largest owners of knowledge assets such as regulations, documents, forms. To build a knowledge-based system (KBS) for e-government has proved to be an effective way to enhance the efficiency of handling governmental services. However, few efforts are made to address automatic reasoning of knowledge-intensive tasks within e-government processes. For this purpose, we present an approach to building an e-government KBS by using the CommonKADS, a knowledge-engineering methodology, and semantic web technologies (OWL, SWRL, OWL-S), with the aiming of automatically solving knowledge-intensive tasks within e-governmental services. Our experiences show that the CommonKADS is crucial to the analysis and identification of knowledge-intensive tasks within government processes, whereas the semantic web technologies enable the refinement of domain ontologies, domain rules and task methods.

A Business Process Management System (BPMS) requires transaction management to guarantee reliability of the business process transactions. Several transaction protocols have been suggested for the transaction management, but they are heterogeneous. This heterogeneity interrupts message exchanges among BPMSs which use different transaction protocols, so that the interoperability among the BPMSs cannot be guaranteed. To solve this problem, this paper suggests a semantics-based protocol for business process transactions. The suggested protocol is composed of the static semantics and the operational semantics. In the context of the static semantics, transaction states and messages are defined using the Web Ontology Language (OWL). In the context of the operational semantics, state transitions of business process transactions are defined using the Abstract State Machine (ASM). The suggested approach is expected to enhance interoperability among heterogeneous BPMSs, to increase the understandability for the transaction protocols, and to support automatic transaction execution and systematic transaction monitoring.

This paper presents a fuzzy version of the semantic view-based search paradigm. Our framework contributes to previous work in two ways: First, the fuzzification introduces the notion of relevance to view-based search by enabling the ranking of search results. Second, the framework makes it possible to separate the end-user’s views from content indexer’s taxonomies or ontologies. In this way, search queries can be formulated and results organized using intuitive categories that are different from the semantically complicated indexing concepts. The fuzziness is the result of allowing more accurate weighted annotations and fuzzy mappings between search categories and annotation ontologies. A prototype implementation of the framework is presented and its application to a data set in a semantic eHealth portal discussed.

We propose a conceptual model for semantic search and implement it in security access control. The model provides security access control to extend the search capabilities. The scalable model can integrate other ontology providing the general ontology as the transformation interface. We combine text Information Retrieval (IR) with semantic inference in the model. So it can not only search the resources and the relationships between them according to the user’s privileges, but also locate the exact resource using text IR. We build a security ontology based on Role-Based Access Control (RBAC) policy. A semantic search system Onto-SSSE is implemented based on the model. The system can perform some complex queries using ontology reasoning, especially about association queries such as the relationships between resources. The evaluation shows that the new system performs better than exiting methods.

For domain ontology construction and expansion, data-driven approaches based on web resources have been actively investigated. Despite the importance of document filtering for domain ontology management, however, few studies have sought to develop a method for automatically filtering out domain-relevant documents from the web. To address this situation, here we propose a document filtering scheme that identifies documents relevant to a domain ontology based on concept preferences. Testing of the proposed filtering scheme with a business domain ontology on 1,409 YahooPicks web pages yielded promising filtering results that outperformed the baseline system.

Geospatial Semantic Web (GSW) has become one of the most prominent research themes in geographic information science over the last few years. The traditional spatial database stores the quantitative data such as coordinate, while GSW needs much qualitative information such as spatial relation. The previous qualitative spatio-temporal systems were all prototype systems which did not support general spatio-temporal relation model and data input. We design the qualitative spatial relation database (QSRDB) based on spatial reasoning. GML data can be converted to QSRDB as data input. OWL ontologies can be generated from QSRDB and applied to GSW systems.

The semantic web represents a major advance in web utility, but it is currently difficult to create semantic-web content because pages must be semantically annotated through processes that are mostly manual and require a high degree of engineering skill. Furthermore, users need an effective way to query the semantic web, but any burden placed on users to learn a query language is unlikely to garner sufficient user support and interest. Unfortunately, both the creation and use of semantic-web pages are difficult, and these are precisely the processes that must be made simple in order for the semantic web to truly succeed. We propose using information-extraction ontologies to handle both of these challenges. In this paper we show how a successful ontology-based data-extraction technique can (1) automatically generate semantic annotations for ordinary web pages, and (2) support free-form, textual queries that will be relatively simple for end users to write.

HStar is implemented to support large scale OWL documents management. Physical storage model is designed on file system based on semantic model of OWL data. Inference and query are implemented on such physical storage model. Now HStar supports characters of OWL Lite and we try to adopt strategy of partial materializing inference data, which is different from most of existing semantic repository systems. In this paper we first give the data model which HStar supports, then give an analysis of our inference strategy; storage model and query process are discussed in detail; experiments for comparing HStar and related systems are given at last.

With the increasing use of ontologies in Semantic Web and enterprise knowledge management, it is critical to develop scalable and efficient ontology management systems. In this paper, we present Minerva, a storage and inference system for large-scale OWL ontologies on top of relational databases. It aims to meet scalability requirements of real applications and provide practical reasoning capability as well as high query performance. The method combines Description Logic reasoners for the TBox inference with logic rules for the ABox inference. Furthermore, it customizes the database schema based on inference requirements. User queries are answered by directly retrieving materialized results from the back-end database. The effective integration of ontology inference and storage is expected to improve reasoning efficiency, while querying without runtime inference guarantees satisfactory response time. Extensive experiments on University Ontology Benchmark show the high efficiency and scalability of Minerva system.

Most of the current workflow-based service composition frameworks and systems require processes to be predefined and services to be statically-bound, thus lacking necessary flexibility to adapt to frequent changes arising from domain/business/user rules and the dynamic Internet environment. This paper proposes a service composition framework based on a flexible workflow method, which enables a part of a process to be created by automatic service composition. In this paper, we propose a semi-automatic service composition framework which enables a part of a process to be created by automatic service composition. In this framework, we encapsulate those uncertain, dynamic and variable parts of a process into black-boxes with a set of rules at the modeling phase. While at the executing phrase, black-boxes are concretized by composing services according to the predefined rules automatically. This framework has been implemented in DartFlow-a service composition platform for the sharing of the TCM (Tradition Chinese Medicine) knowledge and services.

The Semantic Web services has become a challenging research topic in the last half of decade. Various frameworks offer means to semantically describe all the related aspects of Semantic Web services, but the solutions to the heterogeneity problems, inherent in a distributed environment such as the Web, are still to be properly integrated and referred to from the main phases of the Web services usage. Both data and process heterogeneity, as well as the multitude of functionalities required and offered by semantic Web services’ requesters and providers hamper the usability of Web services, making this technology difficult to use. This paper emphasizes the role of mediators in a Semantic Web services architecture, illustrating how the mediators can enable the Semantic Web services usages in operations like discovery, invocation and composition.

Semantic Web makes the automatic discovery and invocation of Web Services become possible. But existing methods perform the capability matching, which is crucial for service discovery, either only according to inputs and outputs (IO), which results in a not very precise matching, or trying to tackle arbitrary services, which results in an undecidable reasoning. In this paper, targeting merely the information-providing type of Web Services, we present a precise and decidable matching method based on the Description Logic reasoner. An outstanding property of our method is that it can determinate the accurate binding of IO between requested and advertised services, which is necessary for automatic invocation yet rarely addressed in previous work. Besides, this paper also describes a useful use case for automatic Web Services discovery and invocation.

This paper proposes a method to automatically generate composite services. The function of a service is specified by its Inputs, Output, Preconditions, and Result (IOPR). These functional descriptions are translated into a first-order logic (FOL) formula. An Automatic Theorem Prover (ATP) is used to generate a proof from known services (as axioms) to the composite service (as an object formula). Based on the deductive program synthesis theory, the implementation of the composite service is extracted from the proof. The “proof to program” method used here guarantees the completeness and correctness of the result. An brief introduction of the prototype system is given.

Much work has been done on automatic information providing Web Service discovery and composition, such as the query rewriting approaches proposed by the database community and planning methods in semantic web research. This paper studies the problem of semantic information providing Web Service composition. More specifically, we propose a new method to represent the semantic information providing Web Services in the CARIN language, which seamlessly integrates both database and semantic web technologies. Then, a semantic rewriting based framework and algorithm are proposed to compose the Web Services. Through a case study we show that the new method could find more compositions compared with both query rewriting and planning based Web Service composition methods.

Automated Web service composition and automated Web service annotation could be seen as complimentary methodologies. While automated annotation allows to extract Web service semantics from existing WSDL documents, automated composition uses this semantics for integrating applications. Therefore applicability of both methodologies is essential for increasing the productivity of information system integration. Although several papers have proposed methods for automated annotation, there is a lack of studies providing analysis of the general structure of Web services. We argue that having an overview of general Web services structures would greatly improve design of new annotation methods. At the same time, progress in automated composition has resulted in several methods for automating Web services orchestration. In this paper we propose application of automated composition also for analysing Web services domain. We identify and analyse some general Web services properties and provide their interpretation in an industrial context.

This paper presents, in a nutshell, a unifying framework for conceptually modeling, formally representing, and executing Semantic Web services. We first introduce a conceptual model for representing Semantic Web services and its design principles, then we present a language based on different logical formalisms used to express Semantic Web services that are compliant with our conceptual model. Finally, a high level overview of an execution environment, and its relations to the conceptual model and the language introduced in this paper, are presented.

We present in this paper the methodology for automatic generation of OWL-S service model ontology along with results and issues. First we extract information related to atomic services and their properties such as IOPE from UML class diagram, and retrieve information related to composition of services from UML state-chart diagram. Then XSLT applications utilize the acquired information to generate the OWL-S service model ontology through the predefined mappings between OWL-S constructs for composite services and UML state-chart primitives. For the justification of generated service ontology several validation checks are performed. Our service ontology generation method is fully automatic and effective in that it is performed in familiar environment to developers and information needed to generate service ontology is provided necessarily during service development. It is also noticeable to facilitate representing the condition with GUI rather than complex language like OCL.

When there do not exist the directly matched services but exist several services in the repository that can be combined to meet the requirements, how to discovery the multiple services and their composition relations are the critical issues. This paper proposes a composition-oriented and AND/OR graph-based service search method named as CoSA, which can automatically search the composition relation graph in concepts level and composition plan in implement level. Composition operator and domain characteristics are reflected in the heuristic functions. CoSA decreases the service search space and improves the search effectiveness. By unifying the service search and composition problems into one composition-oriented service search problem, CoSA enables the dynamic and automatic service composition.

In this paper, we propose a domain ontology construction tool with OWL. The advantage of our tool is focusing the quality refinement phase of ontology construction. Through interactive support for refining the initial ontology, OWL-Lite level ontology, which consists of taxonomic relationships (defined as classes) and non-taxonomic relationships (defined as properties), is constructed effectively. The tool also provides semi-automatic generation of the initial ontology using domain specific documents and general ontologies.

Ontologies have been widely accepted as the primary method of representing knowledge in the Semantic Web. Knowledge Elicitation (KE) is usually one of the first steps in building ontologies. A number of ontology editors such as Protégé have been developed to assist users in building ontologies efficiently. However, traditional KE techniques, such as card sorting and laddering, are not yet supported, but performed manually and outside of such tools. In this paper we present a methodology and a corresponding plug-in for Protégé that allows graphical ellicitation knowledge from documents using card sorting and laddering approaches. Our aim is to seamlessly integrate the KE techniques into the ontology building process to make ontology building more efficient and less error-prone. As a side-effect the persistent storage of card sorting and laddering results allows for later traceability of ontology development. KE largely depends on user interaction with the plug-in, therefore we employed user-centred design principles to capture requirements. After implementation, the plug-in was evaluated thoroughly against the requirements. The evaluation shows that this KE plug-in meets many of the user’s expectations and indeed saves them considerable time when building ontologies.

The paper describes the concept of

topical ontology

and the development of a topical ontology of fraud. A topical ontology is concerned with a set of themes identified to represent the knowledge structure of the domain expert. It reflects the specific scope, perspectives and granularity of conceptualization about the themes. It sits on the base ontology, integrates multiple domain ontology and serves as the knowledge framework for application ontologies. It is architected with a basic conceptual schema and configuration design pattern to capture the knowledge structure as well as concepts and relations of the knowledge.

In order to cope with the rapidly changing product development environment, manufacturing enterprises are forced to collaborate with each other through establishing a virtual organization. In collaboration, designated organizations work together for a mutual gain based on product data interoperability. However, product data interoperability is not fully facilitated due to the semantic inconsistency among product data models of enterprises. In order to overcome the semantic inconsistency problem, this paper proposes a reference ontology called Reference Domain Ontology (RDO) and a methodology for supporting product data interoperability with semantic consistency using RDO. RDO describes the semantics of product data model and metamodel for all application domains in a virtual organization. Using RDO, application domains in a virtual organization can easily understand product data models of others without model transformation. RDO is built by a hybrid approach of

top-down

using an upper ontology and

bottom-up

based on the merging of ontologies of application domains in a virtual organization.

Patient safety is one of the most significant issues not only to medical providers but also to the general public. Despite the widespread recognition of the adverse event reporting for patient’s safety, there is no widely accepted or standardized way to request and report adverse event information. We designed the semantically interoperable Adverse Event Reporting framework. It consists of two components: the Adverse Event Ontology to describe adverse event in semantically interoperable way and the Adverse Event Reporting Schema (AERS) to envelope and deliver the content of adverse event report request and report. The Adverse Event Ontology was built upon existing adverse event taxonomies. The AERS was designed for common adverse event messaging interface in the form of XML Schema. The adverse event reporting framework is expected to allow semantic interoperability in sharing and exchange of patient safety information within and among various healthcare information systems.

Presently, organizations make significant investments in biomedical data and information sources. These investments are expected to produce reduction of errors and quality improvements in data management and analysis. To sustain achievements in quality and efficiency, healthcare organizations need to be vigilant in monitoring the state of competitiveness of their platforms. In the technology post-adoption period, healthcare organizations use multiple data sources to search for technology-related information to maintain technology parity with, or dominance over their competitors. Firstly this study seeks to answer the following research question: what approaches do healthcare organizations employ with regard to managing diverse sources of data and information in order to sustain their technology competitiveness. Then as an initial step in this direction, in this paper we discuss the conceptual foundation for the phenomenon of data and information sources management capability for the proteomics domain. This is done by discussing the case of Protein Data Source Integration by Protein Ontology.

Cross-organizational interoperability and coordination are major challenges to Virtual Organization(VO) applications. In this paper, a semantic Web enabled multi-agent platform for logistic VO supporting is proposed. The issue of extending OWL with multi-attribute constraints for VO modeling is addressed. A constraint rule language

SWOCRL

is proposed which is based on OWL and SWRL with constraint extension and class-scoped restriction. Important VO concepts such as organizations, activities, resources and their logistic specializations are described with OWL plus

SWOCRL.

The particle swarm optimization(PSO) algorithm is a robust stochastic evolutionary algorithm based on the movement and intelligence of swarms.To efficiently retrieve relevant documents from the explosive growth of the Internet and other sources of information access,a PSO-based algorithm for Web document query optimization is presented. Experimental results show that the proposed algorithm can improve the precision of document retrieval markedly compared with relevant feedback and genetic algorithm.

With the growing interest in modular ontology languages to address the need for collaborative development, integration, and use of ontologies on the Web, there is an urgent need for a common framework for comparing modular ontology language proposals on the basis of criteria such as their semantic soundness and expressive power. We introduce an Abstract Modular Ontology (AMO) language and offer precise definitions of semantic soundness such as localized semantics and exact reasoning, and expressivity requirements for modular ontology languages. We compare Distributed Description Logics (DDL),

ε

-connections, and Package-Based Description Logics (P-DL) with respect to these criteria. Our analysis suggests that by relaxing the strong domain disjointedness assumption adopted in DDL and

ε

-connection, as P-DL demonstrated, it is possible to overcome some known semantic difficulties and expressivity limitations of DDL and

ε

-Connections.

Based on the pi-calculus, this paper proposes a kind of ontology process model used for solving the change implementation and propagation problems of ontology evolution process. This solution is discussed at three levels: the change implementation of single ontology evolution, the push-based synchronization realization for the change propagation in the evolution of multiple dependent ontologies within a single node, and the pull-based synchronization realization for the change propagation of the distributed ontologies evolution.

In WordNet, the lexicalized noun/ verb concepts are organized hierarchically by means of hypernymy. As the most basic semantic relation, hypernymy not only serves to construct the specific hierarchy of the concepts in the domain, but also provides a common way of reasoning along the hierarchy for NLP researchers. However, we’ve found two kinds of inappropriate hierarchy in WordNet, the cases of ring and isolator for short. This paper offers a comprehensive study of these cases and make clear that they can cause a degenerate structure, hence harass the reasoning and eventually lead to errors.

In this paper, firstly we put forward an

AO framework

of autonomous ontology, by which a language entity in an ontology is interpreted locally, nevertheless the semantic cooperation is still keeping. Different from various of works based on DDL (Distribute Description Logic [1]),

AO

framework depends on

semantic binding

instead of domain-relation to set up relationship between different ontologies so that it avoids damaging the autonomy of each local ontology. Secondly we formalize the basic operations among ontologies, say

free-access operation

,

importing operation

, and

mapping operation

in the

AO

framework, and give out the proper semantics of them.

The decentralized structure together with the features of self-organ-ization and fault-tolerance makes peer-to-peer network a promising model for information sharing. However, efficient content-based searching remains a serious challenge of large scale peer-to-peer network. In this paper, we present SemreX, a peer-to-peer system for sharing literature documents. Two main features of SemreX networks are 1) semantic supported literature document retrieval function is provided and 2) peers are self-organized into a semantic overlay according to the similarity of documents which belongs to different topics and queries are routed to semantically similar peers to reduce messages. Experiment results show that SemreX improves search efficiency for literature document retrieval in peer-to-peer network.

Web Ontology Language (OWL) is a semantic markup language for describing information on the Web so that machines can process and interpret Web content. OWL expresses information ontologies and has the capability to map all the information on the World Wide Web into a semantic, machine-understandable atlas of information. This article addresses personal information modeling in OWL through enhancing the OWL specification to include such information. It introduces a scheme for identifying personal information and presents an OWL-based design to model personal information without introducing modifications. Some restrictions on certain OWL constructs are necessary to integrate personal information in the language.

Regarding the uncensored nature of the Semantic Web, the question of how much credence to give each information source is a main problem. We cannot expect each user to know the trustworthiness of each source. We tackle this problem by employing a semantic reputation mechanism which enables P2P Semantic Web to utilize reputation mechanism based on semantic similarity among peers. Our experiments show that the system with this mechanism outperforms the system without it. We hope that this method will help move the Semantic Web closer to fulfilling its promise.

The participating nodes exchange information without knowing who is the original sender in P2P networks of basic form. Packets are relayed through the adjacent nodes and do not contain identity information about the sender. Since these packets are passed through a dynamically-formed path and since the final destination is not known until the last time, it is impossible to know who has sent it in the beginning and who will be the final recipient. The anonymity, however, breaks down at download/upload time because the IP address of the host from which the data is downloaded can be known to the outside. We propose a technique to provide anonymity for both the client and the server node in unstructured/structured P2P network. A random node along the path between the client and the server node is selected as an agent node and works as a proxy: the client will see it as the server and the server looks at it as the client, hence protecting the identity of the client and the server from each other.

This paper proposes a map ontology driven approach to natural language traffic information processing, and also describes its evaluation results. Traffic congestion is considered a major urban problem whose solution has long been sought for by engineers and researchers. Recently, the idea of gathering traffic information from mobile users via short message service appears promising. However, the traffic information is difficult to process to achieve a high accuracy because of its direct, indirect and connotative expressions. The proposed map ontology consists of a set of concepts, attributes, relations and constraints on them. The map ontology plays two key roles: 1) a basis for natural language traffic information analysis, and 2) a basis for user query analysis. In this paper we present the major information processing modules and services for mobile users. Experimental results show that the proposed method can improve the traffic information processing accuracy to 93%–95%.

A web-based system for order fulfillment provides a software environment for successfully implementing the build-to-order supply chain (BOSC) strategy. However, current efforts in this domain are not adequate to support automatic reasoning of knowledge-intensive activities within order processing processes and supervision and flexible responsiveness of the entire workflows. Based on the application scenario from a conveyer BOSC, this paper proposes an approach to developing an order management system called OMS-KW enhanced by the Semantic Web and workflow technologies. A multi-ontology-based approach is presented to facilitate representation, sharing and reuse of different types of knowledge. Moreover, multiple ontologies in OWL provide semantic foundation for interoperability between the system and other systems. In addition, problem-solving methods (PSMs) and SWRL-based rules are developed to enable automatic execution of knowledge-intensive activities. Furthermore, the system integrates the knowledge and workflow applications to monitor all the knowledge-intensive and non-knowledge-intensive activities and to improve system flexibility.

Most of the current information retrieval methods are mainly based on keywords matching, and they can not understand the meaning of the keywords. Though some researches have proposed the methods based on domain ontology, it is difficult to implement the general IR because different ontology bases are heterogeneous. Aiming at the questions above, a distributed IR model based on semantic web services (D-IRSW) is proposed. This model puts different Semantic Retrieval Service (SRS) on special ontology base and the results returned by SRS are processed by Semantic Retrieval Service Engine (SRSE). Experiment shows that this model can improve the precision and recall of IR obviously.

We developed an Enterprise Contents Management System for an academic domain. The main feature of this system is its function for focusing searches in Web documents, utilizing human names and locations appearing in the documents as the search context. To realize this function, we adopted a standard text-mining algorithm for extracting proper nouns. We conducted an experimental study of this system against the existing digital contents of our university, and succeeded in efficiently obtaining suitable contents along the given contexts, which were obtained through previous searches. This experiment also suggested that our approach solves the general problem of finding an appropriate set of key words in a Web search. By performing this experiment, we confirmed that context mining is one of the most important technologies to be further developed in our effort to promote knowledge circulation through digital contents.

This paper generalizes the idea of traditional syntactic text autocompletion onto the semantic level. The idea is to autocomplete typed text into ontological categories instead of words in a vocabulary. The idea has been implemented and its application for semantic indexing and content-based information retrieval in multi-facet search is proposed. Four operational semantic portals on the web using the implementation are presented as application cases.

In this paper, we introduce a service where ontology summarizes blogs to get useful in the real stores. In ubiquitous computing environment, it would be desired for users to bind their real world situation and useful information on the Internet. However, the current typical device for ubiquitous computing like a cellular phone has a small display, limited operations, and narrow-band network. Therefore, semantics use to extract only the necessary information and services is for the ubiquitous computing. Ubiquitous Metadata Scouter is for the user to scan products barcodes by cameras of cellular phones. It gets the corresponding metadata to the product from the Internet, and collect the related blogs. Then, it analyzes the contents of each blog referring ontologies, and indicates the total reputation. Also, it shows other related products which are much talked about. This paper illustrates each function of this service and our public experiment at the real consumer electronics store and book store in Tokyo since March 2006. It would provide an instant benefit as a semantics usecase in the ubiquitous computing.

This paper proposes a distributed environment for dementia care that consists of interactive photo annotation and reminiscence content delivery over the Internet by using Semantic Web technologies. We first propose a

Networked Interactive Photo Annotation

service that supports Internet-based collaborative photo annotation among a remote video author and a dementia sufferer and his or her family. This system is built on top of an authoring tool we have developed to assist in reminiscence video production by making use of photo annotation. Combined with an IP video phone, the proposed system is intended to promote conversation between the video author and the dementia sufferer as well as to annotate the shared photo. Next, we present a

Networked Interactive Reminiscence Content Delivery

service that enables a remote dialog partner to initiate communication with the users via an IP video phone in order to deliver reminiscence contents to their display and to share these contents with them.

In this paper, we propose a system that recommends appropriate mobile services from the viewpoint of the user’s task which fits with user’s situation in the real world. Key components are a situation provider that reason on user situation based on context gathered from multiple sources, and a task knowledge base which stores semantic task descriptions of what actions the mobile user is likely to perform in daily life. We present the architecture of the proposed system; the situational reasoning engine which makes use of context ontologies represented using OWL, and the task knowledge base which stores OWL-S-based descriptions of the user’s tasks in the real world. Finally, we describe a prototypical implementation and some realized use cases.