Search

Similarity calculation is the key to solve the question that concept matching in semantic and affects the quality of service composition, and so have strong effect on satisfaction of users. In view of inadequateness, of the current concept similarity calculation that all kinds of factors are not considered comprehensively, the paper proposed the method of internal and cross ontology concept of similarity calculation. Concept similarity calculation in ontology is based on concept tree and takes all factors including all kinds of the relations among concepts into account. Concept similarity calculation across ontology divide into concept of similarity and attribute similarity calculation, and set weights of concept and attribute similarity to obtain the last similarity. So similarity calculation is more comprehensive and accurate.

The video clips only have simple information that these are just recorded data. There is a need to make the video clips actual sensation and look real to satisfy users for resolve the needs. We suggest new video model, called AFVM (Actual Feeling Video Model), that is based on ontology concept. The purpose of this study is to provide AFVM and new format of space where containing divided videos for actual image expression.

This paper presents PORSCE II, a system that combines planning and ontology concept relevance for automatically composing semantic web services. The presented approach includes transformation of the web service composition problem into a planning problem, enhancement with semantic awareness and relaxation and solution through external planners. The produced plans are visualized and their accuracy is assessed.

Semantic web service discovery aims at returning the most matching advertised services to the service requester by comparing the semantic of the request service with an advertised service. The semantic of a web service are described in terms of inputs, outputs, preconditions and results in Ontology Web Language for Service (OWL-S) which formalized by W3C. In this paper we proposed an algorithm to calculate the semantic similarity of two services by weighted averaging their inputs and outputs similarities. Case study and applications show the effectiveness of our algorithm in service match.

Following the advent of information technology and the rapid growth of its application in the medical field, the picture archiving and communication system (PACS) became very popular in mid- to large-scale hospitals. This study aimed to compare the concept lattice of radiology report content before and after the adoption of PACS. This study proposes a formal concept analysis process to produce different levels of ontological concepts from the radiology report. Ontology concept lattice diagrams are presented along with the correlation of concepts and their corresponding significance. The conceptual clustering method is applied to obtain a reasonable number of concepts. To find differences, the structure of ontology is compared in different phases by using a distance measurement. The study results showed a delicate change in radiology report terms before and after the adoption of the system. Given the quantitative analysis results, a qualitative-focused ethnography will be further conducted with several radiologists.

We present a method for using aligned ontologies to merge taxonomically organized data sets that have apparently compatible schemas, but potentially different semantics for corresponding domains. We restrict the relationships involved in the alignment to basic set relations and disjunctions of these relations. A merged data set combines the domains of the source data set attributes, conforms to the observations reported in both data sets, and minimizes uncertainty introduced by ontology alignments. We find that even in very simple cases, merging data sets under this scenario is non-trivial. Reducing uncertainty introduced by the ontology alignments in combination with the data set observations often results in many possible merged data sets, which are managed using a possible worlds semantics. The primary contributions of this paper are a framework for representing aligned data sets and algorithms for merging data sets that report the presence and absence of taxonomically organized entities, including an efficient algorithm for a common data set merging scenario.

It is important for agents to communicate and interact with each other, especially if they are part of the same multi-agent system. In most cases, different agents are working collaboratively towards the same goal. They need to talk to each other, share tasks, exchange results etc. Here, it is important that agents understand each other; for example, they need to speak the same language or be able to translate and understand the language spoken by other agents.

Ontologies are high expressive knowledge models and as such increase the expressiveness and intelligence of a system. Ontologies were introduced into the computer and information community to be used by various agents and for different applications addressing the problems of various knowledge domains.

Semantic information has been paid much attention in web IR. Although many researches have improved the retrieval performance by employing WordNet synset and concept, relations between concepts are often ignored by most of the semantic retrieval methods. We propose a relation enhanced concept vector model CRVM(concept-relation vector model) for document representation in this paper, and the documents to be retrieved are indexed by both concepts and relations. Domain ontology is employed to provide background knowledge for constructing concept based vector representation of documents. We prove the effectiveness of ontology concept and relation enhanced document representation for retrieving by web pages derived from WebKB data set and Open Directory Project.

This article presents conceptual navigation and NavCon, an architecture that implements this navigation in World-Wide Web pages. NavCon architecture makes use of ontology as metadata to contextualize user's search for information. Conceptual navigation is a technique to browse Web sites within a context. Context filters relevant retrieved information. Context also drives user's navigation through paths that meet his needs. Based on ontologies, NavCon automatically inserts conceptual links in Web pages. By using these links, users may navigate in a graph representing ontology concepts and their relationships. Browsing this graph, it is possible to reach documents associated with user's desired ontology concept. An enterprise may implement conceptual navigation to improve user's search for information in a knowledge management environment. Using a ontology to conduct navigation in a Intranet, it is possible to the user have a better understanding about enterprise knowledge structure.

Ontology is increasingly being used to build applications that utilize domain-specific knowledge. How to process ontology-based query efficiently has received many attentions in resent research. The measurement of concept's similarity is basis and foundation of semantic query based on ontology, however, current similarity measurement of ontology concepts involves in artificial intelligence area and psychological area limit efficiency when facing the application that the information is complicated, we propose a model to measure the semantic similarity between concepts on the basis of psychological studies about similarity and artificial intelligence studies about similarity, we express how to implement semantic query. Our approach enables users to reference ontology data directly from SQL using the semantic query operators, and make the ontology-driven applications easy to develop.

Determining the size of an ontology that is automatically learned from text corpora is an open issue. In this paper, we study the similarity between ontology concepts at different levels of a taxonomy, quantifying in a natural manner the quality of the ontology attained. Our approach is integrated in a recently proposed method for language-neutral learning of ontologies of thematic topics from text corpora. Evaluation results over the Genia and the Lonely Planet corpora demonstrate the significance of our approach.

This article makes further study on data needed by automatic construction for Chinese medicinal ontologypsila concept description architecture, reconstructs and uses recognized knowledge in Chinese medicinepsilas domain by theory and technology of NLP. Based on realizing Chinese medicine knowledge description architecturepsilas automatic construction and acquiring successfully, this article use expertspsila knowledge to realize au-learning system of limited textpsilas ontology and try exploring domain ontologypsila evolution .it revolve bottleneck problems of ontology study effectively to lay the data base for Chinese knowledgepsilas dining and use. Untill now, this has been more ideal and applied method and its successful study would be provide theory gist and technology support for professional domain ontologypsilas automatic construction.

This article makes further study on data needed by automatic construction for Chinese medicine ontology' concept description architecture, reconstructs and uses recognized knowledge in Chinese medicine's domain by theory and technology of NLP. Based on realizing Chinese medicine knowledge description architecture's automatic construction and acquiring successfully , this article use experts' knowledge to realize au-learning system of limited text's ontology and try exploring domain ontology' evolution At revolve bottleneck problems of ontology study effectively to lay the database for Chinese knowledge's dining and use.

Ontology is an effective method to express knowledge. Some ontologies are large usually. The large scale of ontology brings a new problem in maintenance, release etc. Ontology can be divided into some small ontologies through ontology partition. It leads to easy use of ontology. Ontology partition method based on ant colony algorithm is presented in the paper. Not only hierarchy relations, but also the other semantic relations are considered to compute concept relativity in the method. Ontology concept hierarchy relation is taken as directed acyclic graph and common disjunctive ancestor is used to calculate concept hierarchy relativity. Ant colony algorithm is adopted to solve ontology partition. Solution construction method and local search method special to ontology partition are given in the paper. Pheromone is laid on concept and applied to construct solutions in the algorithm. Local search is put forward to improve the quality of solutions. Pheromone matrix is updated according to the quality of solutions. The results of experiments shows the method proposed in the paper gains better partition result than the other methods.

The Internet and other open connectivity environments create a strong demand for the sharing of data semantics. Emerging ontologies are increasingly becoming essential for computer science applications. Organizations are looking towards them as vital machine-processable semantics for many application areas. Ontology in general, is an agreed understanding of a certain domain, axiomatized and represented formally as logical theory in a computer resource. By sharing ontology, autonomous and distributed applications can meaningfully communicate to exchange data and make transactions interoperate independently of their internal technologies. Conference management is a service that is offered by event management organizations to clients wishing to run large scale conferences. These services are often not cost effective and require an expert maintenance team. The next wave of improvement would be to leverage on the capabilities of World Wide Web and Web Semantics The main goal of this dissertation is to meet the above-mentioned possibilities by developing a conference management tool using ontology functionality. Ontology provides diverse capabilities in terms of functionalities and flexibility. Defining detailed conference specifications via ontology allows easy, seamless access and passing of information. This dissertation proposes the concept of synergizing ontology and conference management in order to elevate conference management to another level. iv Firstly, an in-depth investigation is done on ontologies to discover all the challenges, strengths and weaknesses. Past inventions using ontologies are researched to identify the flexibility, reusability and compatibility with current technology and requirements. Based on in-depth research and findings, the right programming language and ontology concept is selected that will ensure robustness in the functionality of the system. Secondly, data collected from the Web is identified using the metadata elements and mapped against the ontology schema. Once mapped, the elements are then stored in the database for future use. Finally, the system is deployed and tested to confirm that requirements are met. An evaluation is done to gauge the user’s acceptance towards the system. The results obtained from the evaluation will reinforce whether the initial system requirements were met and how far the system needs improvement in the future. This dissertation is aimed to contribute especially in the implementation of the next generation Web technologies, Dublin Core ontology and Resource Description Framework, in developing conference management tools. WebCon successfully shows the benefit of developing a Web application based on DC and RDF plus how data representation is expressed in a machine understandable form.

Interaction among agents about reputation is essential to accelerate the convergence of the reputation evaluation. Semantic heterogeneity of different reputation models makes agent interaction a problem, especially in open MAS. We propose in this paper a service oriented architecture, SOARI , to deal with this problem. Namely, SOARI is composed of an external Ontology Mapping Service ( OMS ) and an agent internal Translator module. This architecture supports concept mapping and translation among reputation model ontologies to a common ontology and vice-versa, thus allowing heterogeneous agents to interoperate about reputation. We present an example of the OMS 's use, by showing the mapping of two reputation models to a common ontology. Finally, we illustrate the use of the whole SOARI architecture in a simplified electronic commerce scenario. These experiments have enabled us to analyze the limitations and advantages of a hybrid approach for heterogeneous agents interoperation.

Expressing the user competences through domain ontology concepts is a prerogative for developing well managed and semantically enriched user profiles, transferable from a system to another. If, supplementary, the available documents are also ontology-based annotated, the add-on value will concern not only the document semantics, but also the relations and dependencies between users and documents. In such approach, the ontology constitutes the binder between peoples, as well as between peoples and documents, and also between documents. Its reasoning support sustains the development of a collective intelligence, as well as the most suitable knowledge sharing, according to the users common competencies. In this article we present such modeling approach, and also some methods for user and document model development, as well as the advantages for personalized and collaborative facilities.

A sub-symbolic knowledge representation oriented to the enhancement of chat bot interaction is proposed. The result of the technique is the introduction of a semantic sub-symbolic layer to a traditional ontology-based knowledge representation. This layer is obtained mapping the ontology concepts into a semantic space built through Latent Semantic Analysis (LSA) technique and it is embedded into a conversational agent. This choice leads to a chat-bot with “evocative” capabilities whose knowledge representation framework is composed of two areas: the rational and the evocative one. As a standard ontology we have chosen the well-founded WordNet lexical dictionary, while as chat-bot the ALICE architecture. Experimental trials involving four lexical categories of WordNet have been conducted, and an example of interaction is shown at the end of the paper.

In the traditional information service system, the lack of service personalization and semantic information influences the intelligence of information service, and decreases the quality of service. Cooperative recommendation has emerged as an effective technology for personalized information access. In this paper, we present a framework of cooperative recommendation based on ontology construction. We first construct domain ontology, and find user interest through user behavior record database, then construct user interest ontology by the mapping relationship between user interest and domain ontology. Through identifying the vertical weight by user interest similarity, the horizontal weight by the level of ontology concept utilize counted by PageRank, we use the improved weighted association rule algorithm to mining the concepts in user interest ontology, and exploit the user interest model. At last, we realize the semantic-based, personalized cooperative recommendation oriented to content.

ThispaperpresentsanArtificialNeuralNetwork-based(ANN) agent with capabilities for discovering distributed knowledge sources. This agent has the responsibility of guiding knowledge requirements towards distributed ontology domains in the SemanticWeb, indicating i.e. potentially partners for the establishment of a dynamic collaborative relationship. The agent performs its task through a neural network model. This work shows a proposed reference architecture, explains the ontology- matching model ANN-based for the agent and presents preliminary good results obtained.

We designed and implemented a generic search engine (Vaidurya), as part of our Digital clinical-Guideline Library (DeGeL) framework. Two search methods were implemented in addition to full-text search: (1) concept-based search, which relies on pre-indexing the guidelines in a clinically meaningful fashion, and (2) context-sensitive search, which relies on first semi-structuring the guidelines according to a given ontology, then searching for terms within specific labeled text segments. The Vaidurya engine is fully functional and is used within the DeGeL system. We describe the Vaidurya ontological and algorithmic framework; we also briefly summarize the results of a detailed evaluation in the clinical-guideline domain, demonstrating that both concept-based and context-sensitive ontology-independent search are highly feasible and significantly improve on free text search retrieval performance. We conclude by analyzing the limitations and advantages of the approach, and the steps that we have started to take to extend it based on user feedback.

In this paper, we propose a knowledge discovery-based approach to ontology concept design. In our approach, concept design is a stepwise activity which exploits ontology matching techniques in order to retrieve useful external concepts semantically related to the design at hand. This way, the resulting ontology knowledge space is open towards external knowledge sources, by complementing the ontology expert knowledge with domain knowledge stored in other external sources, such as other domain ontologies, Web directories, and, in general, the semantic Web.

In the Web service community, services may be exchanged among distributed environments. Actually, web services are described in terms of ontologies. When ontologies are distributed, arises the problem of achieving sematic interoperability. This problem is undertaken by a process which defines rules to relate relevant parts of different ontologies, called “Ontology Mapping”. The present paper describes a methodology for automatic and semantic mapping of ontologies, basing our approach on a mathematical model called Information FlowModel and denoted IF Model.

Grid computing is innovative information service infrastructure for dynamic and distributed resources sharing and collaboration. Grid workflow is used to handle tasks with control and data dependencies , and plays an important role in grid computing. It is essential to design an appropriate model to satisfy the distributed and heterogeneous workflow systems that must be flexible, reusable, dynamic feature in higher level. As the idea of the designing and composing semantic Web services, a method for designing grid workflow system framework based on ontology is proposed in this paper. Four types of ontology concept are defined: workflow_meta ontology, model_driven method ontology, knowledge representation ontology and date types ontology, and the particular description of their functions, constitutes and relations with each other are given. Based on this framework, the grid workflow systems will have stronger capability to deal with their cooperation and dynamic composition with each other.

As E-business developing, how to friendly and intelligently interact with users in website becomes an important issue. Because of this, the demand of semantic interoperability is expanding too. In order to enhance the collaboration and cooperation of the users and web service providers, this paper proposes a semantic based smart interactive model. The model combines ontology technology. With the help of domain ontology the model is augmented many friendly interactive functions. It is made up of many interactive units. Each of them has consanguineous connections with the domain ontology. Through the relationships of the model and ontology concepts, according to the property connections of each ontology concept, the model achieves the additional functions. The model can be reused expediently. This paper proves the validity of the model through the emulational experiment.

With the rapid development of the Semantic Web, the ontology technology has played an increasingly important role in collaborative System. The concept relatedness measure of heterogeneous ontology can be used to support information retrieval and information sharing among different users. Traditional method to solve the question of similarity between the concepts is based on the concept distance or information content between the two concepts of a single ontology concept tree. This paper presents a hybrid method to calculate the concept relatedness of heterogeneous ontologies. It is divided into two parts: The first is a fixed weighted measure based on the concept of the tree which was combined by multiple heterogeneous ontologies in a mapping way; the other variable calculation is based on users' communications. We have applied this method in our experimental platform IPVita and been proved to be a good one.

The complexity and diversity of geographic data models found on Geographic Information Systems (GIS) allow for different ways to represent the same geographic reality. The increasing use of GIS on organizations has raised the need for georeferenced information interchange among autonomous and heterogeneous sources [9].

There are many initiatives in the scientific community to produce knowledge management and CSCW systems. However, it is difficult to promote the easy information share among learners. In this paper we present Olympus, a multi-agent system to help learners share not only what the information content is, where the information is, and who have the information needed by the learner, but also how to use the available knowledge. Olympus uses agent technologies, ontologies and data mining to create knowledge chains in a semi-automatic way, which is a job that usually would take a lot of effort. The agent monitors the learner's web navigation activities. From there, another agent classifies its content using an ontology, creates and recommends a knowledge chain to the learner. As a sub-product of this work we establish a knowledge base with classified web pages contents.

The concepts of theoretical mechanics have been sufficiently well studied, they are used both for educational purposes and practical application. Nowadays, the use of ontologies is developing rapidly, thus allowing acquiring knowledge about the specific field of application. The author of this research analyses appropriateness of ontologies for the needs of theoretical mechanics. The study shows the use of graphs in the work with taxonomy concepts and describes the key notions of the ontologies. The author has tried to develop the concept of domain ontology for better understanding of the key notions of theoretical mechanics with a help of Protégé, which would be useful for students in the process of studying theoretical mechanics.

This article describes our work realised since the beginning of the Towntology project, which aim was the development of urban ontologies. First of all our work deals with the comprehension of what is an ontology and their uses. Thanks to this prior studies, we develop a prototype and 3 urban ontologies: road system, urban mobility, urban renewal. After describing our result, we synthesize the main difficulties encountered during the development of these ontologies. Keywords: Ontology development, Ontology classification, Towntology prototype, road system ontology, urban mobility ontology, urban renewal ontology. 1. Introduction Since 20 years, we are speaking more and more about ontologies. But what is exactly an ontology ? Are ontologies useful for urban planning? What may be the different uses of ontologies in urban planning? This article tries to answer to these questions through a presentation about ontology evolution and case studies. There are a lot of definitions of ontology notion: philosophical approach, Artificial Intelligence approach, linguistic approach, information retrieval approach, … In this article, we chose the definition of Artificial Intelligence field proposed by Gruber in 1993: an ontology is “

Analyzing the characteristic of multi-Agent and geographic Ontology, The concept of the Agent-based Spatial Information Semantic Grid (ASISG) is defined and the architecture of the ASISG is advanced. ASISG is composed with Multi-Agents and geographic Ontology. The Multi-Agent Systems are composed with User Agents, General Ontology Agent, Geo-Agents, Broker Agents, Resource Agents, Spatial Data Analysis Agents, Spatial Data Access Agents, Task Execution Agent and Monitor Agent. The architecture of ASISG have three layers, they are the fabric layer, the grid management layer and the application layer. The fabric layer what is composed with Data Access Agent, Resource Agent and Geo-Agent encapsulates the data of spatial information system so that exhibits a conceptual interface for the Grid management layer. The Grid management layer, which is composed with General Ontology Agent, Task Execution Agent and Monitor Agent and Data Analysis Agent, used a hybrid method to manage all resources that were registered in a General Ontology Agent that is described by a General Ontology System. The hybrid method is assembled by resource dissemination and resource discovery. The resource dissemination push resource from Local Ontology Agent to General Ontology Agent and the resource discovery pull resource from the General Ontology Agent to Local Ontology Agents. The Local Ontology Agent is derived from special domain and describes the semantic information of local GIS. The nature of the Local Ontology Agents can be filtrated to construct a virtual organization what could provides a global scheme. The virtual organization lightens the burdens of guests because they need not search information site by site manually. The application layer what is composed with User Agent, Geo-Agent and Task Execution Agent can apply a corresponding interface to a domain user. The functions that ASISG should provide are: 1) It integrates different spatial information systems on the semantic The Grid management layer establishes a virtual environment that integrates seamlessly all GIS notes. 2) When the resource management system searches data on different spatial information systems, it transfers the meaning of different Local Ontology Agents rather than access data directly. So the ability of search and query can be said to be on the semantic level. 3) The data access procedure is transparent to guests, that is, they could access the information from remote site as current disk because the General Ontology Agent could automatically link data by the Data Agents that link the Ontology concept to GIS data. 4) The capability of processing massive spatial data. Storing, accessing and managing massive spatial data from TB to PB; efficiently analyzing and processing spatial data to produce model, information and knowledge; and providing 3D and multimedia visualization services. 5) The capability of high performance computing and processing on spatial information. Solving spatial problems with high precision, high quality, and on a large scale; and process spatial information in real time or on time, with high-speed and high efficiency. 6) The capability of sharing spatial resources. The distributed heterogeneous spatial information resources are Shared and realizing integrated and inter-operated on semantic level, so as to make best use of spatial information resources,such as computing resources, storage devices, spatial data (integrating from GIS, RS and GPS), spatial applications and services, GIS platforms, 7) The capability of integrating legacy GIS system. A ASISG can not only be used to construct new advanced spatial application systems, but also integrate legacy GIS system, so as to keep extensibility and inheritance and guarantee investment of users. 8) The capability of collaboration. Large-scale spatial information applications and services always involve different departments in different geographic places, so remote and uniform services are needed. 9) The capability of supporting integration of heterogeneous systems. Large-scale spatial information systems are always synthetically applications, so ASISG should provide interoperation and consistency through adopting open and applied technology standards. 10) The capability of adapting dynamic changes. Business requirements, application patterns, management strategies, and IT products always change endlessly for any departments, so ASISG should be self-adaptive. Two examples are provided in this paper, those examples provide a detailed way on how you design your semantic grid based on Multi-Agent systems and Ontology. In conclusion, the semantic grid of spatial information system could improve the ability of the integration and interoperability of spatial information grid.

Based on analysis of relationship between ontology and conventional information organization and problems existing in ontology construction study and on authors’ experience of building ontology, the paper focuses on currently well accepted domain knowledge and domain experts’ effective domain which are two indispensable terms to quickly and successfully construct a domain ontology. The paper also reconstructs and reuses existing accepted domain knowledge, establishes a set of depended texts’ ontology learning system, and finally realizes automatic construction of domain ontology concept description system through NLP theory and technology. This would further provide theory and technology support for domain ontology automatic construction

http://www.springerlink.com/; The paper presents the outcomes of a practical experiment aimed at the identification of the various types of annotations that can be attached to enterprise strategic data models. The work is part of a more extensive experimentation on different enterprise models perspectives developed inside the ”Semantic Enrichment of Models and Architecture & Platforms” task group of the FP6 IST-508-011 NoE INTEROP, whose goal is to evaluate the appropriateness (and the possible incompleteness) of existing semantic enrichment concepts, techniques, services and tools. Besides the need for multiple ontologies, the experiment enlighten a rather new perspective with respect to the literature on semantic annotation, related to the fact that mathematical objects have to be taken into consideration.

Robust mechanisms for ontology selection are crucial for the evolving Semantic Web characterized by rapidly increasing numbers of online ontologies and by applications that automatically use the associated metadata. However, existing selection techniques have primarily been designed in the context of human mediated tasks and fall short of supporting automatic knowledge reuse. We address this gap by proposing a selection algorithm that takes into account 1) the needs of two applications that explore large scale, distributed markup and 2) some properties of online ontology repositories. We conclude that the ambitious context of automatic knowledge reuse imposes several challenging requirements on selection.

A fuzzy related classification approach for Web document based on ontology concept semantic measurement is presented in this paper. The features of ontology in the semantic web are explored, and a method to compute the semantic similarity between concepts is put forward. Motivated by the semantic similarity and the fuzzy characteristics of the Web document, the fuzzy related technology combined with VSM in classifying Web documents into a predefined set of ontology categories is adopted. Finally some examples are presented to show that the results are satisfying.

In this paper, we define a reference conceptual framework to organize ontology knowledge spaces and related semantic collaboration schemes for coordinated and virtual access to heterogeneous and distributed information resources inside and outside the enterprise, at both intra- and inter-enterprise level under different collaboration requirements and goals. The framework exploits ontology knowledge spaces and enabling services for searching and retrieving the relevant information resources, namely those semantically related to a target request, both in a stable and emergent collaboration scenarios.

To enable accessing web information at semantic level, this paper develops a semantic query planning mechanism on XML based web information system with complex ontology mapping technology. It discusses the patterns of complex ontology mappings at first, and then the ontology-based query planning in Mediator-Wrapper based environment with GAV style querying request. The extension of XML query algebra and XML query planning algorithm are discussed in detail.

Ontologies are increasingly adopted to facilitate the model driven software development (MDSD). The issue of intertransformations among various ontologies is quickly growing prominent. Some explain that variation of ontology definition should be accepted as a must. We would agree with the point that the definition of ontology for the MDSD should be further standardized with tools. In this paper, the ontology definition for the MDSD is systematically analyzed from the philosophical and human cognitional views. Based on a few metaconcepts, ontology creation and evaluation modes are proposed. By providing general precise and consistent semantics for development elements, this framework will considerably improve the development of models of automation oriented development MDSD processes. Experimental applications on intertransformations and unifications of semantics of existing modeling languages are very encouraging.

Ontologies are increasingly used to represent the intended real-world semantics of data and services in information systems. Unfortunately, different databases often do not relate to the same ontologies when describing their semantics. Consequently, it is desirable to have information about the similarity between ontology concepts for ontology alignment and integration. This paper presents the SOQA-SimPack Toolkit (SST), an ontology language independent Java API that enables generic similarity detection and visualization in ontologies. We demonstrate SST’s usefulness with the SOQA-SimPack Toolkit Browser, which allows users to graphically perform similarity calculations in ontologies.

Ontology learning today ranges from simple frequency counting methods to advanced linguistic analyses of sentence structure and word semantics. For ontologies in information retrieval systems, class concepts and hierarchical relationships at the appropriate level of detail are crucial to the quality of retrieval. In this paper, we present an unsupervised keyphrase extraction system and evaluate its ability to support the construction of ontologies for search applications. In spite of its limitations, such a system is well suited to constantly changing domains and captures some interesting domain features that are important in search ontologies. The approach is evaluated against the project management documentation of a Norwegian petroleum company.

To offer a semantically suitable service for user in context-aware system, ontology concept is needed. By using the ontology, it is possible to provide knowledge sharing and support for syntactic and semantic interoperability. In this paper, we propose the Context-Aware Service Engine based on Ontology. As we use ontology, our system has the following useful aspects. First, our system can describe types, hierarchies, relations of contexts, so that any context instance can be accommodated into the system with no additional effort. Seconds, as we design two level's ontology, any system which uses ontology could reuse our context ontology context in pervasive environment. Three, our system could be applied to semantic web which is called a revolution of a post web and could provide interoperability.

Because there is still no agreed-upon global ontology, Web services supplied by different providers typically have individual and unique semantics, described by independently developed ontologies. The seamless connection of these distributed Web services for business-to-business applications depends heavily on reconciling the disparate semantics, possibly by integrating the ontologies. In this paper, we describe an approach to reconcile ontologies from distributed Web services. Our approach is totally automated, and features the following: i) alignment of the ontologies is performed without previous agreement on the semantics of the terminology in each ontology; ii) both linguistic and contextual features are considered; iii) the use of WordNet for linguistic analysis; iv) integration of heuristic knowledge for contextual analysis; and v) inference of new relationships by applying several rules based on domain-independent relationships and property lists. Experiments have been carried out to show the promising results of our system.

In this article, we propose a new ontology evolution approach that combines a top-down and a bottom-up approach. This means that the manual request for changes (top-down) by the ontology engineer is complemented with an automatic change detection mechanism (bottom-up). The approach is based on keeping track of the different versions of ontology concepts throughout their lifetime (called virtual versions). In this way, changes can be defined in terms of these virtual versions.

Data integration is the process by which data from heterogeneous data sources are conceptually integrated into a single cohesive data set. In recent years agents have been increasingly used in information systems to promote performance. In this work we propose a modeling framework for agent oriented data integration to demonstrate how agents can support this process. We provide a systematic analysis of the process using real world scenarios, taken from email messages from citizens in a local government, and demonstrate two agent oriented data integration tasks, email routing and opinion analysis.

Ontology Integration plays a key role in information integration systems, especially in the semi-structured information integration systems. This paper develops an ontology integration mechanism which is based on the complex semantic mapping to avoid the insufficient of simple and direct semantic mapping. It introduces an ontology-based extension to the XML query algebra at first, and discusses the ontology-based query mechanism, which includes ontology integration procedures and XML query rewriting mechanism secondly.

Currently there appear only few practical semantic web applications. The reason is mainly in that a large number of existed web documents contain only machine-unreadable information on which software agent can do nothing. There have been some works devoting to web document annotation manually or semi-automatically to solve this problem. This paper presents an automatic approach for web document annotation based on specific domain ontology. Because complete semantic annotation of web document is still a tough task, we simplify the problem by annotating ontology concept instances on web documents and propose an Ontology Instance Learning (OIL) method to extract instances from structure and free text of web documents. These instances of the ontology concept will be used to annotate web pages in the related domain. Our OIL method exhibits quite good performance in real life web documents as shown in our experiment.

Different concept and attribute definitions for geographical features underlying information systems make it difficult to share geographical information. This paper provides concept brokering methods based on upper level ontology for retrieval of heterogeneous geographical information. The methods include design of upper level ontology using Concept Lattices. The user ontology is associated with domain ontology through upper level ontology by concept brokering rules. An example for the upper level ontology of transportation is given to illustrate the concept brokering methods.

Security patterns are best security practices.We identified them as a suitable tool for novices supporting them in solving security problems more efficiently. Nevertheless, there are still some features missing in order to take real benefit from them (see Section 5.8.2). The basic problem is to find the “right” security pattern. Due to a lack of defined syntax it is not possible to ask meaningful questions and to get semantically meaningful results. Therefore, we develop a theoretical model for security patterns in this chapter. The fundamental idea is to share security patterns (and related information) utilizing the ontology paradigm. Based on a security core ontology (see Chapter 6) we can define the syntax of security patterns at a different level. The result is a model for security patterns that helps to understand what security patterns precisely are and that enables sophisticated search and retrieval of security patterns.

We investigate the possibility of web information discovery and extraction by means of a modular architecture analysing separately the multiple forms of information presentation, such as free text, structured text, URLs and hyperlinks, by independent knowledge-based modules. First experiments in discovering a relatively easy target, general company descriptions, suggests that web information can be efficiently retrieved in this way. Thanks to the separation of data types, individual knowledge bases can be much simpler than those used in information extraction over unified representations.