Semantic Technology

Graphical user interfaces design in software development process focuses on maximizing usability and the user's experience, in order to make the interaction for users easy, flexible and efficient. In this paper, we propose an approach for evaluating the usability satisfaction degree of a web-based system. The proposed method has been accomplished in two phases and implemented on an airlines website as a case study. In the first phase, a website usability test is implemented by a number of users, and then the results obtained are translated into charts for a final web-based system evaluation in the second phase. The results achieved were satisfactory, since the places where the weaknesses and gaps in the website are identified and recommended solutions to avoid them are drawn. The authenticity of the results have been confirmed by comparing them with user opinions acquired from a questionnaire, which proves the precision in which the website is rated.

In this article I describe software that facilitates “question-centric curricula” in which big questions, rather than academic disciplines, are the primary means of organizing educational resources. To find these questions, the software scans course catalogs and extracts all sentences ending in a question mark. To find connections between questions and courses, I present several computational techniques. One leverages the Library of Congress system; another implements so-called semantic technology that uses huge numbers of simple internet searches to ascertain the meaning of texts. The software assembles the results and shows, in one image, how every course at an institution relates to a given question.

Question classification is very important for question answering. This paper present our research work on question classification through machine learning approach. In order to train the learning model, we designed a rich set of features that are predictive of question categories. An important component of question answering systems is question classification. The task of question classification is to predict the entity type of the answer of a natural language question. Question classification is typically done using machine learning techniques. Different lexical, syntactical and semantic features can be extracted from a question. In this work we combined lexical, syntactic and semantic features which improve the accuracy of classification. Furthermore, we adopted three different classifiers: Nearest Neighbors (NN), Naïve Bayes (NB), and Support Vector Machines (SVM) using two kinds of features: bag-of-words and bag-of n grams. Furthermore, we discovered that when we take SVM classifier and combine the semantic, syntactic, lexical feature we found that it will improve the accuracy of classification. We tested our proposed approaches on the well-known UIUC dataset and succeeded to achieve a new record on the accuracy of classification on this dataset.

International Journal of Web & Semantic Technology (IJWesT) is a quarterly open access peer-reviewed journal that provides excellent international forum for sharing knowledge and results in theory, methodology and applications of web & semantic technology.

Submissions of proposals are very often a tedious affair. Proposals which are submitted goes through not only a complex and tedious process but often the scrutiny of many individuals of different roles. Hence, it is important that any automation envisaged goes through a meticulous exercise to achieve the same. Proposal Submission System aims to provide an online proposal submission mechanism, improving the traditional and physical methods of submission. Such system allows assignment submission to be more efficient and greater rigor. Online submission provides electronic copy of assignments, which has many benefits over traditional physical copy submission of assignments. With the implementation of Proposal Submission System, one can be subjected to the same rigor as traditional means without compromising on quality whilst adhering to the same process workflow.

Graphical user interfaces design in software development process focuses on maximizing usability and the user's experience, in order to make the interaction for users easy, flexible and efficient. In this paper, we propose an approach for evaluating the usability satisfaction degree of a web-based system. The proposed method has been accomplished in two phases and implemented on an airlines website as a case study. In the first phase, a website usability test is implemented by a number of users, and then the results obtained are translated into charts for a final web-based system evaluation in the second phase. The results achieved were satisfactory, since the places where the weaknesses and gaps in the website are identified and recommended solutions to avoid them are drawn. The authenticity of the results have been confirmed by comparing them with user opinions acquired from a questionnaire, which proves the precision in which the website is rated.

This is an ethnographic case-study of research and development practices taking place in an interdisciplinary project between education and computer sciences. The Ensemble-project, part of the Technology Enhanced Learning programme (2008-12), has studied case-based learning in a number of diverse settings in Higher Education, working to develop semantic technologies for supporting that learning. Focussing on one of the six research settings, the discipline of archaeology, the current study has had three purposes. By opening up to scrutiny the practices of research and development, it has firstly sought to understand how a shared research question is answered in practice when divergent research approaches are brought to bear upon it. Secondly, the study has followed the emergence of a piece of semantic technology through these practices. The third aim has been to assess the advantages and disadvantages of Actor-Network Theory (ANT) in studying unfolding, open-ended processes in real time. Through critical ethnographic participation, multiple ethnographic research methods, and by drawing on ANT as theoretical practice, the study has shown the precarious and unpredictable nature of research and development work, the political nature of research methods and how multiple realities can be produced using them, and the need for technology development to flexibly respond to changing circumstances. We have also seen the mutual adoption and extension of practices by the two strands of the project into each others’ domains, and how interdisciplinary tensions resolved, while they did not disappear, through pragmatic changes within the project. The study contributes to the interdisciplinary fields of Science and Technology Studies (STS) where studies on the ‘soft sciences’, such as education, are few, and a new field of Studies in Social Science and Humanities (SSH) which is emerging alongside and from within the STS. Interdisciplinary endeavours between fields pertaining largely to the natural and the social sciences respectively have not been studied commonly within either field.

Knowledge sharing within a large entity such as government organizations, is critical to successful e-government implementations. Semantic technologies offer promise in this regard, however, many studies in the past have suggested that the semantic technologies for knowledge sharing suffer from potential weaknesses such as dynamicity, scalability, flexibility and offer limited options for specific business applications. In most cases the need for knowledge integration in business interactions in government systems are overlooked or loosely addressed due to rapidly changing situations and complex business networking. Significant challenges remain in developing e-government solution that can address the need for growing knowledge integration and sharing to enhance business interactions. This paper outlines a knowledge sharing framework to solve these issues with respect to citizen's participation in egovernment system, by encouraging user driven activities through the use of emerging technology and ontology based design.

The compass of Cloud infrastructure services advances steadily leaving users in the agony of choice. To be able to select the best mix of service offering from an abundance of possibilities, users must consider complex dependencies and heterogeneous sets of criteria. Therefore, we present a PhD thesis proposal on investigating an intelligent decision support system for selecting Cloud-based infrastructure services (e.g. storage, network, CPU). The outcomes of this will be decision support tools and techniques, which will automate and map users' specified application requirements to Cloud service configurations.

FAIA covers all aspects of theoretical and applied artificial intelligence research in the form of monographs, doctoral dissertations, textbooks, handbooks and proceedings volumes. The FAIA series contains several sub-series, including "Information Modelling and Knowledge Bases" and "Knowledge-Based Intelligent Engineering Systems". It also includes the biennial ECAI, the European Conference on Artificial Intelligence, proceedings volumes, and other ECCAI-the European Coordinating Committee on Artificial Intelligence-sponsored publications. An editorial panel of internationally well-known scholars is appointed to provide a high quality selection.

Abstract: Although ontologies promise an effective technology for information integration, it is often the case that two or more information providers do not share the same ontology. Several (semi)-automated ontology mapping methods have been developed towards solving this problem. This paper presents AUTOMS-F, a framework implemented as a Java API, which aims to facilitate the rapid development of tools for automatic mapping of ontologies by synthesizing several individual ontology mapping methods. Towards this goal, AUTOMS-F provides a highly extensible and customizable application programming interface. AUTOMS is a case study ontology mapping tool that has been implemented using the AUTOMS-F framework, and has been successfully evaluated in the international OAEI 2006 contest.

It is evident that companies and research centres can find a myriad of instruments to fund their R&D (Research & Development) activities. Due to the dynamics of the information management in these circumstances there is a need for intermediary businesses intervention. Consequently, intermediary companies are thus involved in a complex process that needs to be managed and controlled. Within this scenario an Information Technology (IT) platform, named RDi-Advise, was developed by EgeoIT using semantic technologies to support R&D process decisions. This case analysis describes the development and implementation of the platform including the lessons learned during the activity period.

The rapid increase in the publication of knowledge bases as linked open data (LOD) warrants serious consideration from all concerned, as this phenomenon will potentially scale exponentially. This paper will briefly describe the evolution of the LOD, the emerging worldwide semantic web (WWSW), and explore the scalability and performance features of the service oriented architecture that forms the foundation of the semantic technology platform developed at MIMOS Bhd., for addressing the challenges posed by the intelligent future internet. This paper concludes with a review of the current status of the agriculture linked open data.

Graphical user interfaces design in software development process focuses on maximizing usability and the user's experience, in order to make the interaction for users easy, flexible and efficient. In this paper, we propose an approach for evaluating the usability satisfaction degree of a web-based system. The proposed method has been accomplished in two phases and implemented on an airlines website as a case study. In the first phase, a website usability test is implemented by a number of users, and then the results obtained are translated into charts for a final web-based system evaluation in the second phase. The results achieved were satisfactory, since the places where the weaknesses and gaps in the website are identified and recommended solutions to avoid them are drawn. The authenticity of the results have been confirmed by comparing them with user opinions acquired from a questionnaire, which proves the precision in which the website is rated.

ABSTRACT Evaluating inter-organizational relationships (IORs) is important in todays businesses for increasing competitiveness and business potential. Typically, IORs are measured by high-level key performance indicators (KPIs) such as trust, knowledge sharing, and others. However, these high-level KPIs are difficult to be measured quantitatively. It is therefore difficult to determine IORs and their outcomes since the evaluation of IORs results in a complex and ambiguous task. In this vision paper, we propose a set of research questions dealing with measuring and evaluating IORs. Based on these research questions, we define a conceptual framework including (i) the identification of KPIs from inter-organizational processes in combination with business information derived from EDIFACT messages and (ii) the alignment of KPIs to business goals by means of the Balanced Scorecard methodology and semantic technology. Having the approach at hand supports us in lifting operational information to the business level. The alignment between KPIs and business goals allows evaluating an organizations' IORs and results in two distinct advantages. First, the explicit connection between KPIs and business goals results in a justification of the relation between IORs and business achievements. Second, the evaluation of IORs against strategic goals can be achieved semi-automatically.

Abstract. This paper describes semantic-based device description which will be designed and implemented in the IST-2005-034891 project HYDRA (“Ne-tworked Embedded System Middleware for Heterogeneous Physical Devices in a Distributed Architecture”) funded within the FP6 IST Programme. HYDRA project aims at development of middleware for intelligent networked embedded system based on service-oriented architecture, deployable on both new and ex-isting networks of distributed wireless and wired devices. The embedded servi-ce-oriented architecture will provide interoperable access to data, information and knowledge across heterogeneous platforms. These devices and their local networks will also be interconnected through broadband and/or wireless ne-tworks. An implemented HYDRA middleware and a toolkit will be validated in real end-user scenarios in three different user domains: Facility management (smart/intelligent homes), Healthcare, and Agriculture. One of the most impor-tant aspects o...

Dietary menu planning for diabetic patients is a complicated tasks involving specific and common-sense knowledge. Case-based approach has been used to provide recommendation in the case where ratings were not easily available for domains such as menu planning. Among the important but yet difficult tasks in the case-based approach is case adaptation. To successfully support case adaptation, the constraint-based approach and food composition ontology were employed. Constraints knowledge were represented as production rules and exploits the food ontology to support adaptation. An ontological approach is also proposed to perform the inference process to satisfy the multiple design constraints.

Water depletion is critical in the dry tropics due to drought, increased development and demographic or economic shifts. Although educational initiatives have improved urban indoor water-use, excessive outdoor wastage still occurs because in most urban areas residential users only have a biannual reading of quantity available to make informed or educated decisions on necessary or unnecessary consumption. For example, the average consumer will water lawns during a designated non-restricted time. The amount of water they use is determined arbitrarily (i.e., either by sight or by blocks of time). In many cases, water is wasted due to over saturation, automated sprinklers that cannot sense precipitation, poor placement of sprinkler direction, etc. Outdoor water use efficiency could be maximized if water flow was shut off when an area of lawn has had sufficient water based on a more intelligent monitoring system. This paper describes the development of an intelligent water management and information system that integrates real-time sensed data (soil moisture, etc) and Web-available information to make dynamic decisions on water release for lawns and fruit trees. The initial pilot-prototype combines Semantic Technologies with Internet of Things to decrease urban outdoor water-use and educate residents on best water usage strategies.

Regulatory processes are normally tracked by regulatory bodies in terms of monitoring safety, soundness, risk, policy and compliance. Such processes are loosely framed processes and it is a considerable challenge for data scientists and academics to extract instances of such processes from event records and analyse their characteristics e.g. if they satisfy certain process compliance requirements. Existing approaches are inadequate in dealing with the challenges as they demand both technical knowledge and domain expertise from the users. In addition, the level of abstraction provided does not extend to the concepts required by a typical data scientist or a business analyst. This paper extends a software framework which is based on a semantic data model that helps in deriving and analysing regulatory reporting processes from event repositories for complex scenarios. The key idea is in using complex businesslike templates for expressing commonly used constraints associated with the de...

On March 14-15, 2006, at the US National Institute of Standards and Technology (NIST) in Gaithersburg, MD, there took place the first Upper Ontology Summit (UOS). This was a convening of custodians of several prominent upper ontologies, key technology participants, and interested other parties, with the purpose of finding a means to relate the different ontologies to each other. The result is reflected in a joint communiqu��, directed to the larger ontology community and the general public, and expressing a joint intent to build bridges ...

This report describes the first five SEALS Evaluation Campaigns over the semantic technologies covered by the SEALS project (ontology engineering tools, ontology reasoning systems, ontology matching tools, semantic search tools, and semantic web service tools). It presents the evaluations and test data used in these campaigns and the tools that participated in them along with a comparative analysis of their results. It also presents some lessons learnt after the execution of the evaluation campaigns and draws some final conclusions.

Academic research almost without exception involves literature searches. The huge wealth of literature can be sorted using ontologies and eventually an ontologically based system may be able to extract relevant literature for researchers based on some simple queues such as research title or hypothesis. In this paper we introduce an ontology-based digital library system and detail the first component of the system that allows real time flexible ontology management. The flexibility aspect includes the modification of the ontology at any time, as well as full real time graphical representation and editing. We introduce our novel semi-formal representation scheme for ontologies that promotes ontology modifiability and adaptability. (Abstract)

Abstract. This paper describes the IST-2005-034891 project HYDRA (“Networked Embedded System Middleware for Heterogeneous Physical Devices in a Distributed Architecture”) funded within the FP6 IST Programme. HYDRA project aims at development of middleware for intelligent networked embedded system based on service-oriented architecture, deployable on both new and existing networks of distributed wireless and wired devices. The embedded service-oriented architecture will provide interoperable access to ...

Through the application of semantic technologies to describe Open Educational Resources, any agent (human or software-based) could process and understand its contents, therefore, the agent could perform tasks autonomously or in a more effective way. In this paper, we describe the design and validation of the OER-CC ontology, which models the domain knowledge of educational resources licensed under Creative Commons Licenses. One of the most important contributions of this work is that we implement different rules and axioms to identify inconsistencies between rights provided by a licensed on an learning material and particular uses that are performed on it.

smartFIX is a product portfolio for knowledgebased extraction of data from any document format. smartFIX automatically determines the document type and extracts all relevant data for the respective business process. Data that is uncertainly recognized is forwarded to a verification workplace for manual checking. In general, users have no difficulties to interpret the document data and wonder why the system needs additional input. For that reason, we will integrate an explanation component that will be used to justify uncertain extraction results, thus, increasing confidence of users. The component will be based on semantic technologies in general and on a semantic log in particular. The log will contain all process relevant information enabling the explanation facility to generate customized and understandable explanations. In this paper, we will discuss the benefits of that kind of technology with reference to DAS.

Semantic technologies are in the process of revolutionizing the way we store, access, and communicate digital information. It is vital that information professionals be conversant in the foundational concepts upon which these technologies are based. This article uses two implementations of semantic technologies, the semantic web and the semantic medline project, to introduce the key ideas of semantic technologies to readers.

smartFIX is a product portfolio for knowledgebased extraction of data from any document format. smartFIX automatically determines the document type and extracts all relevant data for the respective business process. Data that is uncertainly recognized is forwarded to a verification workplace for manual checking. In general, users have no difficulties to interpret the document data and wonder why the system needs additional input. For that reason, we will integrate an explanation component that will be used to justify uncertain extraction results, thus, increasing confidence of users. The component will be based on semantic technologies in general and on a semantic log in particular. The log will contain all process relevant information enabling the explanation facility to generate customized and understandable explanations. In this paper, we will discuss the benefits of that kind of technology with reference to DAS.

Regulatory processes are normally tracked by regulatory bodies in terms of monitoring safety, soundness, risk, policy and compliance. Such processes are loosely framed processes and it is a considerable challenge for data scientists and academics to extract instances of such processes from event records and analyse their characteristics e.g. if they satisfy certain process compliance requirements. Existing approaches are inadequate in dealing with the challenges as they demand both technical knowledge and domain expertise from the users. In addition, the level of abstraction provided does not extend to the concepts required by a typical data scientist or a business analyst. This paper extends a software framework which is based on a semantic data model that helps in deriving and analysing regulatory reporting processes from event repositories for complex scenarios. The key idea is in using complex businesslike templates for expressing commonly used constraints associated with the definition of regulatory reporting processes and mapping these templates with those provided by an existing process definition language. The efficiency of the architecture in evaluation, compliance and impact was done by implementing a prototype using complex templates of Declare ConDec language and applying it to a case study related to process instances of Australian Company Announcements.

I. INTRODUCTION The extensive deployment of digital libraries over the last decades is hardly surprising. They offer remote access to articles, journals and books with many users able to access the same document at the same time [1]. Through the use of search engines, they make it ...

Abstract In this paper, the main challenges of applying ICT in policy modeling are described and a solution is proposed, which emphasizes policy impact exploration, monitoring and risk management. State of the art of policy modeling is given, with the summary of those ...

Private banking is a business area in which the investor requires tailor-made advice. Because of the current market situation, investors are requiring answers to difficult questions and looking for assurance from wealth managers. Private bankers need to have deep knowledge about an innumerable list of products and their characteristics as well as the suitability of each product for the client's characteristics to be able to offer an optimal portfolio according to client expectations. Client and portfolio diversity calls for new recommendation and advice systems focused on their specific characteristics. This paper presents PB-ADVISOR, a system aimed at recommending investment portfolios based on fuzzy and semantic technologies to private bankers. The proposed system provides private bankers with a powerful tool to support their decision process and help deal with complex investment portfolios. The system has been evaluated in a real scenario obtaining promising results.

The compass of Cloud infrastructure services advances steadily leaving users in the agony of choice. To be able to select the best mix of service offering from an abundance of possibilities, users must consider complex dependencies and heterogeneous sets of criteria. Therefore, we present a PhD thesis proposal on investigating an intelligent decision support system for selecting Cloud-based infrastructure services (e.g. storage, network, CPU). The outcomes of this will be decision support tools and techniques, which will automate and map users' specified application requirements to Cloud service configurations.