38,442 research outputs found

    State-of-the-art on evolution and reactivity

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    This report starts by, in Chapter 1, outlining aspects of querying and updating resources on the Web and on the Semantic Web, including the development of query and update languages to be carried out within the Rewerse project. From this outline, it becomes clear that several existing research areas and topics are of interest for this work in Rewerse. In the remainder of this report we further present state of the art surveys in a selection of such areas and topics. More precisely: in Chapter 2 we give an overview of logics for reasoning about state change and updates; Chapter 3 is devoted to briefly describing existing update languages for the Web, and also for updating logic programs; in Chapter 4 event-condition-action rules, both in the context of active database systems and in the context of semistructured data, are surveyed; in Chapter 5 we give an overview of some relevant rule-based agents frameworks

    A Gentle Introduction to Epistemic Planning: The DEL Approach

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    Epistemic planning can be used for decision making in multi-agent situations with distributed knowledge and capabilities. Dynamic Epistemic Logic (DEL) has been shown to provide a very natural and expressive framework for epistemic planning. In this paper, we aim to give an accessible introduction to DEL-based epistemic planning. The paper starts with the most classical framework for planning, STRIPS, and then moves towards epistemic planning in a number of smaller steps, where each step is motivated by the need to be able to model more complex planning scenarios.Comment: In Proceedings M4M9 2017, arXiv:1703.0173

    Concepts and Methods from Artificial Intelligence in Modern Information Systems – Contributions to Data-driven Decision-making and Business Processes

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    Today, organizations are facing a variety of challenging, technology-driven developments, three of the most notable ones being the surge in uncertain data, the emergence of unstructured data and a complex, dynamically changing environment. These developments require organizations to transform in order to stay competitive. Artificial Intelligence with its fields decision-making under uncertainty, natural language processing and planning offers valuable concepts and methods to address the developments. The dissertation at hand utilizes and furthers these contributions in three focal points to address research gaps in existing literature and to provide concrete concepts and methods for the support of organizations in the transformation and improvement of data-driven decision-making, business processes and business process management. In particular, the focal points are the assessment of data quality, the analysis of textual data and the automated planning of process models. In regard to data quality assessment, probability-based approaches for measuring consistency and identifying duplicates as well as requirements for data quality metrics are suggested. With respect to analysis of textual data, the dissertation proposes a topic modeling procedure to gain knowledge from CVs as well as a model based on sentiment analysis to explain ratings from customer reviews. Regarding automated planning of process models, concepts and algorithms for an automated construction of parallelizations in process models, an automated adaptation of process models and an automated construction of multi-actor process models are provided

    Business and Information System Alignment Theories Built on eGovernment Service Practice: An Holistic Literature Review

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    © 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution 3.0 License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.This chapter examines previous studies of alignment between business and information systems holistically in relation to the development of working associations among professionals from information system and business backgrounds in business organization and eGovernment sectors while investigating alignment research that permits the development and growth of information system, which is appropriate, within budget and on-time development. The process of alignment plays a key role in the construction of dependent associations among individuals from two different groups, and the progress of alignment could be enhanced by emerging an information system according to the investors’ prospects. The chapter presents system theory to gather and analyze the data across the designated platforms. The outcomes classify that alignment among business and information system departments remains a priority and is of worry in different ways in diverse areas, which provides prospects for the forthcoming discussion and research.Final Published versio

    SPEC Kit 356 Diversity and Inclusion

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    Today, diversity is defined beyond racial and ethnic groups and includes gender, sexual orientation, ability, language, religious belief, national origin, age, and ideas. The increase of published literature about cultural competencies, microaggressions, and assessment of diversity issues, as well as the inclusion of social justice movements in libraries, suggests diversity-related activities have increased and evolved over the last seven years. Over this time span, several libraries have obtained funding to support strategies to increase the number of minority librarians on their staff and support their advancement within the organization. There also appears to be an increase in the number of diversity or multicultural groups at the local, state, and national levels. However, these changes have not been consistently documented. Therefore, it is important to re-examine this topic to evaluate the impact of evolving endeavors, to see if more ARL libraries are involved, to see how diversity plans have changed over the years, and to document the current practices of research libraries. The main purpose of this survey was to identify diversity trends and changes in managing diversity issues in ARL libraries through exploring the components of diversity plans and initiatives since 2010, acknowledge library efforts since the 1990s, provide evidence of best practices and future trends, and identify current strategies that increase the number of minority librarians in research libraries and the types of programs that foster a diverse workplace and climate. The survey was conducted between May 1 and June 5, 2017. Sixty-eight of the 124 ARL member institutions responded to the survey for a 55% response rate. Interestingly, only 22 of the respondents to the 2010 SPEC survey participated in this survey, but this provides an opportunity to explore the diversity and inclusion efforts of a new set of institutions in addition to seeing what changes those 22 institutions have made since 2010. The SPEC Survey on Diversity and Inclusion was designed by Toni Anaya, Instruction Coordinator, and Charlene Maxey-Harris, Research and Instructional Services Chair, at the University of Nebraska-Lincoln. These results are based on responses from 68 of the 124 ARL member libraries (55%) by the deadline of June 12, 2017. The survey’s introductory text and questions are reproduced below, followed by the response data and selected comments from the respondents. The purpose of this survey is to explore the components of diversity plans created since 2010, identify current recruitment and retention strategies that aim to increase the number of minority librarians in research libraries, identify staff development programs that foster an inclusive workplace and climate, identify how diversity programs have changed, and gather information on how libraries assess these efforts

    A MULTI-FUNCTIONAL PROVENANCE ARCHITECTURE: CHALLENGES AND SOLUTIONS

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    In service-oriented environments, services are put together in the form of a workflow with the aim of distributed problem solving. Capturing the execution details of the services' transformations is a significant advantage of using workflows. These execution details, referred to as provenance information, are usually traced automatically and stored in provenance stores. Provenance data contains the data recorded by a workflow engine during a workflow execution. It identifies what data is passed between services, which services are involved, and how results are eventually generated for particular sets of input values. Provenance information is of great importance and has found its way through areas in computer science such as: Bioinformatics, database, social, sensor networks, etc. Current exploitation and application of provenance data is very limited as provenance systems started being developed for specific applications. Thus, applying learning and knowledge discovery methods to provenance data can provide rich and useful information on workflows and services. Therefore, in this work, the challenges with workflows and services are studied to discover the possibilities and benefits of providing solutions by using provenance data. A multifunctional architecture is presented which addresses the workflow and service issues by exploiting provenance data. These challenges include workflow composition, abstract workflow selection, refinement, evaluation, and graph model extraction. The specific contribution of the proposed architecture is its novelty in providing a basis for taking advantage of the previous execution details of services and workflows along with artificial intelligence and knowledge management techniques to resolve the major challenges regarding workflows. The presented architecture is application-independent and could be deployed in any area. The requirements for such an architecture along with its building components are discussed. Furthermore, the responsibility of the components, related works and the implementation details of the architecture along with each component are presented

    Past, present and future of information and knowledge sharing in the construction industry: Towards semantic service-based e-construction

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    The paper reviews product data technology initiatives in the construction sector and provides a synthesis of related ICT industry needs. A comparison between (a) the data centric characteristics of Product Data Technology (PDT) and (b) ontology with a focus on semantics, is given, highlighting the pros and cons of each approach. The paper advocates the migration from data-centric application integration to ontology-based business process support, and proposes inter-enterprise collaboration architectures and frameworks based on semantic services, underpinned by ontology-based knowledge structures. The paper discusses the main reasons behind the low industry take up of product data technology, and proposes a preliminary roadmap for the wide industry diffusion of the proposed approach. In this respect, the paper stresses the value of adopting alliance-based modes of operation
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