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This paper brings out the limitations of Semi-structured based web mining i.e. Web 2.0 Technologies to an end and applying the feasibility of Structured based mining — Semantic Web/ Web 3.0 to implement the proposed methodology as the Recruiter's Assistant/Training Library Tool. Semantic Web which represents data over web not only for display, but also for machine to understand -Meaningful Retrieval of Data. Ontology is a powerful and efficient way of data retrieval where Mining gives satisfactory results. The Training Library Tool based upon the semantic web capabilities like Interoperability, Knowledge Extraction, Knowledge Consistency Check, Rule-based Reasoning and Machine Learning. The information in the Library Tool can be processed based on ontologies in order to effectively transform information into knowledge which is highly utilized in automated decision making. The proposed semantic web based Library Tool will assist the recruiters in assessing the candidate by tracking both the qualitative of the Organization (i.e. QR) as well as the skill set of the candidate and lead to rational decision for recommendation. During the interview session, recruiters will be aided dynamically based on the progress of interaction between the recruiter and candidate while throwing the question and verifying the answer and simultaneously analyzing the capability of candidate to proceed to higher complexity level according to the skill set of the candidate. [ABSTRACT FROM PUBLISHER]

The deployment of the semantic web depends on the rapid and efficient construction of the ontology. Ontologies also play an important role in biomedicai informatics and in knowledge management. Ontology arouses widespread concern in the artificial intelligence domain and it has been applied extensively. IDSS add artificial intelligence (AI) functions to traditional DSS with the aim of guiding users through some of the decision making phases. In this paper, the development of data analysis in intelligent decision support system(IDSS) based on ontology are proposed. The experimental results indicate that this method has great promise. [ABSTRACT FROM PUBLISHER]

Ontology is the representation of knowledge. It can make knowledge sharable and reusable by managing it efficiently. The utility of knowledge resource can be exploited more effectively. This paper introduced ontology into the field of software-component description and retrieval, proposes a framework of ontology evolution, présentes the semantic information among the components more precisely, makes component oriente service and have semantic reasoning functions, realizes dynamic retrieval of the component, improves recall and precision of the component greatly, and lay foundation, for component inventory, retrieval, assembly and so on. [ABSTRACT FROM PUBLISHER]

As the practice of Enterprise Architecture (EA) diversifies, the schematic management of its objects, semantics and relationship continues to be complex. Given that EA provides support for the IT environment by simulating alignment between dynamic business architectures, heterogeneous application systems and incongruent technologies, the need to ensure validation of conceptualized EA models has become also critical. As a relatively new discipline, its disparate and widespread methodologies makes it even more challenging to adopt a generic approach in which models can be verified sequel to the unavailability of unified EA modelling languages able to describe a wide range of Information Technology domains. This paper seeks to present an approach for addressing this challenge through the use of ontologies and queries based on constraints specified in the model's motivation taxonomy. The paper is experimental research-based and grounds its hypothesis on initial model created using the ArchiMate modelling language. By transforming its conceptual metamodel into a model instance, a process which can be achieved irrespective of the modeling language used in the design of the EA, it represents extracted triples as resource description framework schema (RDFS) by mapping the model artefacts directly into classes and slots using a more conventional web ontology language. The generated RDF is then queried using Protocol and RDF Query Language (SPARQL) adopting the Behavior Driven Development (BDD) concept. A case study of the Student Internship Program (SIP) is deployed to translate information from business needs to IT solutions encapsulating a view of abstraction of the EA. The paper also proposes an implementation of the approach using an open source platform that allows construction of domain models and knowledge-based applications with ontologies and is a contribution towards effective validation of EA through taxonomy decomposition, systematic generation of testable EA artifacts, creation of structural triples of model elements and alignment of motivational goals to business behavior specifications. [ABSTRACT FROM PUBLISHER]

The paper describes the process of complex technical object design on the example of the aircraft, using information technology such as CAD/CAM/CAE-systems. The paper discloses a weight design process, which is associated with all stages of aircraft development and its production. Knowledge-oriented approach of the CTO design gives the possibility of managing geometrical and weight model parameters on all stages of the CTO design. Such structure of automatized CTO design system allows taking into account classic and innovative methods of CTO design, combining them in accordance with their exactness at the calculation composition of CTO parameters. [ABSTRACT FROM PUBLISHER]

Policy/decision makers in governments, corporations and institutions all need to anticipate the future, analysis its impacts and be confidence about the consensus results. Future studies methods are often made to utilize quantitative and qualitative approaches using various methods such as Trend Impact Analysis (TIA). This paper introduces advanced knowledge-based trend impact analysis that integrates the enhanced Trend Impact Analysis, Structural Analysis, Ontology-based Real-Time Delphi and Explanation knowledge-based models to support the policy/decision makers with the impacts of wildcards on the future revenues and provide him to be more confident about the consensus results. This advanced knowledge-based Trend Impact analysis takes into account the benefits of knowledge sharing and explanation capabilities for generating the futures scenarios. The inputs of new TIA matrices are based on the knowledge of nominated and weighted large scale futurists and experts. The main contribution of this paper is the developed idea enhances the participatory approach for traditional TIA and overcomes different challenges of efficiency and effectiveness in the knowledge acquisition process. Also, this idea of knowledge-based TIA is novel, its implementation as a web-based tool and applied it to help policy/decision makers, in the Egyptian ministry of agriculture, for addressing the futures of the national food security. [ABSTRACT FROM PUBLISHER]

Ontology is a technique for expressing formal specification. It is a conceptualization of domain and its terms and relationships. The technique of ontology finds its application in almost every area, some of which includes medicine, e-commerce, chemistry, education etc. Concept clustering is the foremost step in construction of ontology. Concept clustering is usually a manual process involves labor and time intensive task. Hence there is a need for automatic grouping of concepts for ontology construction. In this paper, automatic concept clustering is attempted through data mining clustering techniques. The training set for the concepts formation of ontology structure is obtained from zoo dataset in UCI Machine Learning Repository. The clustering techniques are implemented through Weka 3.7.6, an open source data mining tool. Performance of clustering techniques viz., EM, Farthest First and K-Means are analyzed. It is found that Farthest-First clustering technique yielded the best performance with an accuracy of 93.0693%. The methodology proposed in this paper can be adopted for any other case study also. [ABSTRACT FROM PUBLISHER]

The field of question answering is a very fertile area of research. Till now most of the work that has been done in this area is either in open or closed domain. Restricted domain question answering is emerging as more appropriate and challenging area of research. This paper presents a generic architecture for development of a restricted domain question answering system with a focus on domain knowledge. The paper emphasizes on intelligently combining the domain knowledge and NLP resources in different stages of development of the system. [ABSTRACT FROM PUBLISHER]

To meet the demand of the digital representation for relative information of the electronic medical records, this paper presents a method to converse the existing data and establish electronic medical record repository based on ontology. Furthermore, the electronic medical record storage structure is discussed. The ontology frame is introduced in detail. In order to provide the intelligent reasoning capability, variable rough set theory is applied in the experiment, the reliable EMR samples and reducing decision table are essential for the reasoning result. Finally, the paper tries to research the patients' semantic information and their relations, discover the potential valuable knowledge, assist the doctors carry on effectively early treatment. The experiment result showed that the ontology based description for EMR is efficient for presenting the hospital knowledge structure, available to afford useful sources of information for physician. [ABSTRACT FROM PUBLISHER]

The paper describes the creation of the Knowledge Management System (KMS) based on Lessons Learned documents that were prepared at the Institute of Doctrine of the Military Academy. The objective of the KMS is to provide an access to the available information for the preparation of troops for foreign missions in a user-friendly way. The paper presents the research methodology, the analysis of the documents, the creation of ontology and the KMS development. One of the requirements for the solution was the implementation of the batch information input and the automation of the information context creation. [ABSTRACT FROM PUBLISHER]

Traditional Chinese painting is a unique form of art and highly regarded for its theory, expression and techniques throughout the world. However, popular image processing techniques have little been used in this specific domain. Especially, how to model traditional Chinese painting images based on ontology is a very important and urgent task. In the paper, the characteristics of traditional Chinese painting are analyzed firstly. Then, the process of constructing ontology for traditional Chinese painting is dissertated in details, including how to select appropriate classes and properties in CRM ontology and how to extend them in specific domain. In addition, the framework of retrieval is introduced. Ontology is a good avenue for knowledge sharing and information integration. The work of the paper is very meaning to information standardization in specific Chinese art image domain. [ABSTRACT FROM PUBLISHER]

The paper briefly discusses techniques of semi-automatic detection of outdated knowledge within the framework of Ontological Semantic Technology. Following an overview of the architecture and functionality of Ontological Semantic Technology, the paper illustrates, based on specific examples, how subsumption gaps are detected, and historical and evolving knowledge is incorporated into the ontology. [ABSTRACT FROM PUBLISHER]

Various studies indicate that having concise and consistent identifiers improves the quality of the source code and hence impacts positively source code understanding and maintenance. In order to write concise and consistent identifiers, however, developers need to have some knowledge about the concepts captured in the source code and how they are named. Acquiring such knowledge from the source code might be feasible only for small systems, while it is not viable for large systems. In this paper, we propose an automated approach which exploits concepts and relations automatically extracted from the source code to suggest identifiers. The suggestion is ranked based on the context in which a new identifier is introduced and it can be used either to complete the identifier being written or to replace it with a more appropriate one. To validate the proposed approach, we have conducted a case study by simulating the activities of a developer in naming identifiers. The results of the study show that in the majority of the cases our approach provides completion suggestions which match the identifiers actually used by the developers. [ABSTRACT FROM PUBLISHER]

Many critical multi-agent applications require flexibility in both, individual and collective agent behavior that cannot be addressed by existing models. An example could be an agent system destined for unexpected situation handling and recovery. The paper proposes a framework to model unexpected and exceptional situations relying on goal-oriented situated planning viewpoint integrating both knowledge-based and behavior-based ideas. The paper introduces an ontology-based knowledge model, Scenario Knowledge Base framework which represents experts' knowledge about agent capabilities to act as well as a syntactic behavior patterns structure given over the set of actions the agents are capable to execute. This framework is supported by reusable software core intended for an on-line situated planning that uses the former to dynamically infer all possible courses of actions of agents of a multi-agent system to achieve ultimate goal starting from current agent states. [ABSTRACT FROM PUBLISHER]

With the rapid growth of Web services and the need of quickly finding the right services, automatically clustering Web services becomes exceedingly important and challenging. The main drawback of current clustering algorithms is needs to get total services or a service training set to mine the service attribute. This does not suit for the dynamic distributed environment. In order to address this problem, this paper first raises the concept of service ability and gives a method to compute the service ability. By means of ontology, this paper presents a novel service clustering algorithm based on service ability. Without priori knowledge or similarity computation between any two services, this clustering algorithm can cluster the services with similar function and service ability. Facilitated by this algorithm, a service searching algorithm has been proposed. Experimental and theoretical results show that the clustering algorithm can reflect the services' function clustering feature effectively and searching algorithm can filter a lot of unrelated service. [ABSTRACT FROM PUBLISHER]

Natural language processing relies heavily on resources. Most common usage scenarios include using the resources for automated lexical tagging or named entity recognition. Also manually annotated language resources are used for benchmarking of new automated approaches. To allow any processing on a large scale and considering the complexity of natural language (words can have multiple meanings within the same general context) the resources have to be quite large. In this paper we focus on lexical resources in ontology form. [ABSTRACT FROM PUBLISHER]

Nowadays ontologies are more and more often put on work in diverse industrial areas thanks to their high potential of applying. In this paper we extend work of other developer groups that are interested in ontologies and purvey frameworks for ontology using. To make clear meaning of ontology, we describe it with a set of properties that points out its diversity. Next we focus on possibilities of using ontologies in diagnostic systems with emphasize of interoperability. We illustrate several scenarios for engaging ontologies into these systems for sharing diagnostic datasets or terms meanings of dynamical systems that cause their better understanding and manipulation with them. Each scenario include role of ontology and a list of advantages that ontology implementation brings. [ABSTRACT FROM PUBLISHER]

As the search efficiency is not high and it's difficult to find user's interested information, this paper proposes the combination of ant colony algorithm and ontology to create search engine. By the clear formal specification of body shared concept, the search engine has intelligent search features, and then it can use ontology to provide users' interested search results. In the process of ontology's usage, in order to make different ontology interoperate, the paper introduces similarity computing, and then improves it. Based on the characteristics of ant colony algorithm, it introduces multi-pheromone to change search engine strategy, so it can improve search engine efficiency. While the multi-pheromones apply to different servers, with the increase of search times, it can make the finding of best path more effective. [ABSTRACT FROM PUBLISHER]

Artificial Transportation Systems (ATS) provide a comprehensive perspective to study actual transportation systems, which are a kind of open and complex giant system referring to diverse engineering and social disciplines. To make use of achievements from related research fields, ontology for ATS is constructed in this paper. Besides conceptual model involved in modeling and applications of ATS, the compatibility with other ontology is considered. Further, an ontological knowledge base with SOA (Service-Oriented Architecture) is designed to manage information and knowledge in ATS. The architecture and interfaces of the knowledge base are presented. Benefit from this, construction and applications of ATS can be conducted on a uniform information and knowledge platform. A case study about traffic jam pattern is demonstrated. [ABSTRACT FROM PUBLISHER]

The technology of web 2.0 especially social networking has changed people's behavior, attitudes, interactions, and relationships. User activities on social networking sites have created both explicit and implicit relationship. The relations can be distinguished for the sites with symmetric and asymmetric relationship types. In this paper, we propose a framework for semantic social network analysis for recommending user member groups on social media sites that combines explicit and implicit relationship. The framework utilizes semantic technology, i.e. ontology and RDF, to integrate the resulted data from different sites. Moreover, a presentation of a ontology design for user and activities referring to social network sites. An example of the integrated user profile is demonstrated using FOAF vocabulary. [ABSTRACT FROM PUBLISHER]

The new form of education called "E-Learning" has grown significantly, especially in training institutions (Universities, Schools, Businesses, etc.). Consequently, they develop their software needs assessment in order to assess the information, and allow the learner to correct his knowledge autonomously. The teaching of languages takes place in the context of distance education and involves several research areas, as automatic processing of natural language and modeling of learning action in distance education environment. Therefore, the development of a remote Evaluation system for Arabic requires the preparation of various linguistic tools such as analyzers In this paper we focus on the development of a Morphological Analyzer In Arabic Language which can be operated in a remote evaluation system of the Arab that support during the seventh year basic level grammar taught in Tunisia. This work proposes to establish morphological analysis by promoting treatments that can be used by a system as the decomposition of a text, determining the properties of a word, the search in a text…, these treatments support learning through an explanation of ambiguous words, the integration strategies of Arabic grammar and solving exercises. [ABSTRACT FROM PUBLISHER]

With the continuous evolution and convergence of wireless technologies, mobile devices and sensors, the mobile, ubiquitous and pervasive learning have appeared next to the e-learning to re-organize, on the one hand, the way users interact with the technology, and on the other hand, to provide users a permanent and transparent access to information and contextual services in any time, everywhere and in all situations. Lots of works have already been done in mobile and pervasive learning domain on how to integrate the learning process to work whatever the place, time, work individual or collective and integrate of the mobile and pervasive devices in broader training scenarios, and contexts. The pervasive learning systems are context-aware; the main requirement is to adapt them to the changes of context (learner profile, location, mobile devices, and environment). In this paper, we try to answer to the request what and how do we adapt in pervasive learning system. In the first step, we propose an approach focused on the skills and not only on the acquisition of knowledge, we rely on the use of learning situations contextualized based on learning and tasks evaluation to make significant learning by modifying the learning scenario model used in literature. The adaptation of the pervasive learning system must be flexible which allows to the learner for example to answer a question in different ways (using the palette of terms or by typing the solution…); therefore it is necessary to adapt the interface of interaction by adapting the information, their presentation and selecting the media and the media related factors such as image or video quality and size…. [ABSTRACT FROM PUBLISHER]

Design of a new curriculum and revision of an existing curriculum are considered as tedious tasks for academics. This process requires considerable amount of man hours from subject matter experts in several areas. In this paper, we present a human-assisted semi-automated solution for the design and revision of curricula for degree programmes. We postulate the curriculum design and revision as an ontology modelling process. The solution has been developed as a plug-in, named as OntoCD, for the popular ontological modelling environment, Protégé. A curriculum developer can customize OntoCD by introducing benchmark domain ontology of a certain degree, and loading a skeleton curriculum for the intended degree programme. Alternatively, the domain ontology can be used to design a curriculum on the visual interface provided, and proceed to improve it. The developer can also use OntoCD to load a known curriculum and to do the modification to align with the benchmark domain ontology. The power of OntoCD exemplifies during the process of editing and improving a curriculum. In this process, OntoCD handles many tasks including the credit balancing with core and elective modules, guidance to choose elective modules to meet local needs and resolving name confusions of modules by ensuring an identity of a degree within the respective area. At this stage, OntoCD has been informally tested by designing a Computer Science degree curriculum according to benchmark domain ontology of ACM/IEEE guidelines for computing degrees. The results show that OntoCD guides the developer by reducing the burden due to clerical mistakes, oversights and negligence of some aspects in the development process. [ABSTRACT FROM PUBLISHER]

Wireless sensors are used for monitoring environments such as climate change, water quality and disaster management. Disaster management is a critical and emergent operation now, especially tsunami warning and prediction system. The Indian National Centre for Ocean Information Services (INCOIS) runs a tsunami early warning system for mitigation of oceanogenic disasters. The early warning system comprises of systems like seismic stations, Bottom Pressure Recorder (BPR) and tide gauges. The critical task of the warning system is interpretation of the complex multidimensional data generated by various sensors and interoperability among the systems and handling of heterogeneous data. The issues are in developing a methodology to integrate heterogeneous data received from various components of tsunami early warning system and providing web based data service. To address these requirements importance is given to both syntactic and semantic nature of the data. The syntactic part is responsible for the interoperability of the sensor data. Interoperability is addressed by using Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) framework. Ontologies are used as a means for solving the information heterogeneity problems because of their capability to provide explicit meaning to the information. In this paper we propose a Service Oriented Architecture (SOA) model for the interoperability of sensor networks data and semantics of the data. The purpose of the paper is to provide more meaningful information for Tsunami early warning system using ontology and Jena rule representation. [ABSTRACT FROM PUBLISHER]

Decision makers must know if their cyber assets are ready to execute critical missions and business processes. Net-work operators need to know who relies on a failed network asset (e.g. IP address, network service, application) and what critical operations are impacted. This requires a mapping between net-work assets and the critical operations that depend on them, cur-rently a manual and tedious task. In addition, because of the dy-namic nature of networks and missions, manual mappings of network assets to operational missions rapidly become outdated. This paper describes one approach to modeling the complex rela-tionships between cyber assets and the missions and users that depend on them, using an ontology developed in conjunction with practitioners and cyber mission assurance researchers. We de-scribe the “Camus” (cyber assets, missions and users) proof of concept, which uses this ontology and automatically populates that model from data already on the network. We discuss the technical approach and provide examples of query results re-turned by the model. We conclude by describing ongoing work to enhance this proof of concept and its potential applicability to support mission assurance and mission impact solutions. [ABSTRACT FROM PUBLISHER]

Medical imaging plays an important role in the diagnosis, prognosis and treatment of cancer. Quantitative and qualitative data about medical images are vital components of a radiological report and are very important to the oncologist that requests the radiological exams. However, traditional methods to register these data are inefficient and error prone. The use of unstructured free text in radiology reports makes it impossible to perform even simple calculations, such as changes in lesion dimensions. It also makes the aggregated analysis of many reports difficult. Free text reports lack a reference to the image regions of the finds they refer to and are not machine-computable. This paper proposes a method to provide support for collaborative work among radiologists and oncologists (providing care or taking part in clinical trials) using an imaging web tool, ePAD, to generate structured radiology reports that can be machine-computable. It also shows how ePAD uses Rad Lex ontology terms and the Annotation and Image Markup (AIM) language (and templates) to generate the reports. [ABSTRACT FROM PUBLISHER]

This paper introduces a web-based semantic tool that provides more detailed information about a term selected by the user of a web browser, the Clinical Eye. This tool was initially designed for the medical area of cardiology, which is still controversial in terms of vocabularies. An ontology has been developed as a reference base where those different vocabularies converge. The information supplied by the tool was taken from specialized medical web pages and technical documents. It is a tool of low interference for ongoing activities, so it can be used during a clinical activity. It has been designed according to requirements raised by studies in various medical communities which pointed the use of internet during consultations and medical needs for deep information. [ABSTRACT FROM PUBLISHER]

The increasing complexity for the management of current distributed software and system needs new solutions. Designing autonomic systems which are self-managing and context aware is a solution and also a challenge. This paper proposes the FRAME SELF framework, a generic autonomic architecture based on context awareness and decision models built. The proposed solution capabilities are illustrated on the self-configuration of machine to machine networks (M2M). M2M needs to connect thousands of various fix and mobile machines that are widely distributed and evolve frequently according to their profile and context changes. FRAME SELF uses multi models representation based on ontologies and graphs to describe the M2M concepts and relationship on a multi-level knowledge base. Two communication patterns modules based on service-oriented and event-driven communications are dynamically selected and configured in deployment plans. A M2M smart metering use case is experimented to illustrate the proposed approach. [ABSTRACT FROM PUBLISHER]

The large diversity and heterogeneity of collaborating objects and services in modern networked environments such as personal, vehicular or home networks makes difficult the efficient configuration, deployment and management of composite dynamic systems without a major participation of human actors. This paper proposes an autonomic architecture based on decision models built on ontologies and aimed at self-configuring and self-adapting service-oriented and event-driven distributed systems. Our solution follows a top-down approach based on well-known and accepted standards and implemented as an ecosystem-wide ontology aimed at characterizing the properties of services and events related to consumers and producers entities participating in the autonomic collaborative environment. [ABSTRACT FROM PUBLISHER]

The paper proposes a recommendation mechanism to enhance the managerial training in project-oriented organizations (POOs). The mechanism is presented within the framework of an innovative system used to provide support to POOs during the acquisition and implementation of training services. The recommender engine has, as inputs, the knowledge gaps of the employees given by an assessment system and the alignment in RDF/XML format between two ontological representations: one for the management documents provided by POOs and one for the training curriculum offered to the POOs. The recommender engine makes suggestions for adapting the training curriculum to the POOs' needs, by translating the ontology alignment result into a user-friendly form and by identifying web resources suitable to fill up the knowledge gaps. The outputs are smart recommendations meant to personalize the training curriculum to POOs and, thus, to increase the competitiveness of POOs. [ABSTRACT FROM PUBLISHER]

A Business Intelligence (BI) system can provide information in a reliable, instantaneous and automatic way in order to support crucial decisions of companies as well as of governments. The first step for the implementation of a BI system is the development of the ontology, which can be performed via an institutional glossary. However, usually the link between the ontology and the BI system is not direct, and therefore the implementation of the BI system may be slow. In this paper, we show the application of concept maps for BI system implementation. We exemplify this application using the study case of the implementation of the BI system for the Federal Property Department (SPU), which belongs to the Ministry of Planning, Budget and Management (MP) in Brazil. Besides the efficient implementation via concept maps, the impacts of our proposed BI system are also highlighted in this paper. [ABSTRACT FROM PUBLISHER]

The paper presents an interdisciplinary project which is a work in progress towards a 3D Geographical Information System (GIS) dedicated to Cultural Heritage with a specific focus application on the Castle of Shawbak, also known as the “Crac de Montréal”, one of the best preserved rural medieval settlements in the entire Middle East. The Shawbak archaeological project is a specific and integrated project between medieval archaeological research and computer vision done thanks to a long cooperation between University of Florence and CNRS. Focusing mainly on stratigraphical analysis of upstanding structures we provide archaeologists a two-step pipeline. First a survey process using photogrammetry, both in a traditional way and using the most advanced technique for obtained dense map and then a tool for statistical analysis. The photogrammetric survey is driven by an archaeological knowledge which is formalized by ontologies as a link between all the archaeological concepts which are surveyed. The archaeological knowledge studied is now limited to stratigraphy of upstanding structure using a stone by stone survey as well as a 3D reprojection of archaeologist design made on photographs. The 3D GIS is the last step of this chain and aims the automatic production of 3D models through archaeological database queries: these 3D models are in fact a graphical image of the database and at the same time the interface through which the user is able to modify it and produce different kind of analyzing. All these developments are written in Java within ARPENTEUR framework. [ABSTRACT FROM PUBLISHER]

This paper proposes a general framework for a system with a semantic browsing and visualization interface called Knowledge Communication, Collaboration and Creation Browser (KC3 Browser) which integrates multimedia contests and web services on the grid networks, and makes a semantic mash-up called knowledge workspace (k-workspace) with various visual gadgets according to user's contexts (e.g. their interests, purpose and computational environments). KC3 Browser also achieves a link-free browsing for seamless knowledge access by generating semantic links based on an arbitrary knowledge models such as ontology and vector space models. It assists users to look down and to figure out various social and natural events from the web contents. We have implemented a prototype of KC3 Browser and tested it to an international project on risk intelligence against natural disaster. [ABSTRACT FROM PUBLISHER]

Universal Networking Language (UNL) is an artificial language for computers to represent human language using graphs. UNL system consists of UNL Ontology, which provides the semantic background for each Universal Words (UWs) or concepts. UNL Ontology includes possible relations between UWs, UWs definition and UNL system hierarchy. UNL Ontology store all these information in a lattice structure, where UWs are inter-connected through relations including hierarchical relations such as icl (a-kind-of) and iof (an-instance-of). However, it is difficult for human to visualize the UNL ontology. To solve this problem, we have developed a web system to visualize UNL Ontology. This paper describes the web system and its real life applications. [ABSTRACT FROM PUBLISHER]

The recent years have witnessed a rapid development in virtual reality technology and computer aided design, which accompanied by a vast amount of 3D content springing up from various domains, has given rise to an emerging need for methods by which they can be efficiently annotated before being searched and retrieved. In this paper a new approach to semantic annotation on 3D content is proposed. In this approach, much of the manual work on annotation is replaced with a semi-automatic process based on prior gathering of domain expertise. The geometric properties of objects and their spatial relationships are first automatically extracted and associated with a general ontology, the result of which is then matched against a set of user-defined rules to create annotations represented in an application ontology. The approach is Web3D oriented so that it can take advantage of features of X3D format. It will be shown using a prototype system how this approach can succeed in accelerating the annotation process. [ABSTRACT FROM PUBLISHER]

Ontology is an explicit specification of knowledge as formal description of concepts, relations between the concepts and axioms about the target domain. Ontology is also used to represent user profiles in personalized web information gathering. For representing user profiles many models have been developed, these models provide knowledge from either a global or local knowledge base. The global analysis uses existing global knowledge bases and to produce effective performance. The local analysis observes user behavior in user profiles. The user background knowledge can be better discovered and represented if we integrate global and local analysis. However, it is challenging to use semantic relations of “kind-of”, “part-of”, and “is-a” and synthesize commonsense and expert knowledge in a single computational model. In this paper, a personalized ontology model based on user profiles is used. This model learns user profile from both global knowledge base and local instance repositories. After comparing with benchmark models in web information gathering ontology model has an edge over other models [ABSTRACT FROM PUBLISHER]

The semantic search promises to provide more accurate results than the current keyword matching-based search by understanding user intent and the contextual meaning of terms based on knowledge base. However, the ordinary users have difficulty in using the complex formal query language and the knowledge base schema on Smart TV having the restricted UI/UX. So, it is needed to develop a semantic search system to interpret the meaning of simple user keywords and find the multimedia content users want for Smart TV. In this paper, we describe a framework for the semantic multimedia contents retrieval. It is ontological knowledge base-driven framework in the sense that the knowledge base plays a main role in the whole search process including keyword interpretation and contents search. We also present our prototype system developing to test our framework ideas. [ABSTRACT FROM PUBLISHER]

Automation industry is moving towards more complex systems which are posing new challenges for operation from both machine and human perspectives. A group of challenges is related to management of the overwhelming information flow and to usability of the systems, and context-aware solutions have been recently introduced to the automation field in order to cope with challenges of this kind. The context awareness is seen as a solution which would allow to both the technological system and the human operator to infer the optimal decisions and to behave in the most effective way. In order to reach this capability, the external physical world and the system must be described in a way both interprétable for humans and machines. Ambition of this paper is to contribute to the context-aware (re)configuration of the system with a tool, which is designed to improve the efficiency of the configuration phase of a context-aware system. The tool provides a solution to configure and model the field devices of a system via automatically generated ontologies. This research is a part of a device management framework for a building automation use case, which is targeting to support controlling decisions of dwellers, technical support and social services. [ABSTRACT FROM PUBLISHER]

This paper is an early report of our continuing effort to provide a platform-independent framework so that information originators and security administrators can specify access rights to information consistently and completely, and that this specification is then rigorously enforced. To accomplish this objective it is necessary to link a security policy model to a policy language with sufficient expressive power to ensure logical consistency. For the purposes of this research we are using a modified Attribute-Role-Based Access Control (ARBAC) security model and the Web Ontology Language (OWL) with additional rules in a logic programming framework to express access policy, going beyond the limitations of previous attempts in this vein. In addition we are developing a mechanism using knowledge compilation techniques that allows access policy constraint checking to be implemented in real-time, via a bit-vector encoding that can be used for rapid run-time reasoning. [ABSTRACT FROM PUBLISHER]