11,773 research outputs found

    Discovering Beaten Paths in Collaborative Ontology-Engineering Projects using Markov Chains

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    Biomedical taxonomies, thesauri and ontologies in the form of the International Classification of Diseases (ICD) as a taxonomy or the National Cancer Institute Thesaurus as an OWL-based ontology, play a critical role in acquiring, representing and processing information about human health. With increasing adoption and relevance, biomedical ontologies have also significantly increased in size. For example, the 11th revision of the ICD, which is currently under active development by the WHO contains nearly 50,000 classes representing a vast variety of different diseases and causes of death. This evolution in terms of size was accompanied by an evolution in the way ontologies are engineered. Because no single individual has the expertise to develop such large-scale ontologies, ontology-engineering projects have evolved from small-scale efforts involving just a few domain experts to large-scale projects that require effective collaboration between dozens or even hundreds of experts, practitioners and other stakeholders. Understanding how these stakeholders collaborate will enable us to improve editing environments that support such collaborations. We uncover how large ontology-engineering projects, such as the ICD in its 11th revision, unfold by analyzing usage logs of five different biomedical ontology-engineering projects of varying sizes and scopes using Markov chains. We discover intriguing interaction patterns (e.g., which properties users subsequently change) that suggest that large collaborative ontology-engineering projects are governed by a few general principles that determine and drive development. From our analysis, we identify commonalities and differences between different projects that have implications for project managers, ontology editors, developers and contributors working on collaborative ontology-engineering projects and tools in the biomedical domain.Comment: Published in the Journal of Biomedical Informatic

    Graph-based discovery of ontology change patterns

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    Ontologies can support a variety of purposes, ranging from capturing conceptual knowledge to the organisation of digital content and information. However, information systems are always subject to change and ontology change management can pose challenges. We investigate ontology change representation and discovery of change patterns. Ontology changes are formalised as graph-based change logs. We use attributed graphs, which are typed over a generic graph with node and edge attribution.We analyse ontology change logs, represented as graphs, and identify frequent change sequences. Such sequences are applied as a reference in order to discover reusable, often domain-specific and usagedriven change patterns. We describe the pattern discovery algorithms and measure their performance using experimental result

    A new technique for intelligent web personal recommendation

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    Personal recommendation systems nowadays are very important in web applications because of the available huge volume of information on the World Wide Web, and the necessity to save users’ time, and provide appropriate desired information, knowledge, items, etc. The most popular recommendation systems are collaborative filtering systems, which suffer from certain problems such as cold-start, privacy, user identification, and scalability. In this thesis, we suggest a new method to solve the cold start problem taking into consideration the privacy issue. The method is shown to perform very well in comparison with alternative methods, while having better properties regarding user privacy. The cold start problem covers the situation when recommendation systems have not sufficient information about a new user’s preferences (the user cold start problem), as well as the case of newly added items to the system (the item cold start problem), in which case the system will not be able to provide recommendations. Some systems use users’ demographical data as a basis for generating recommendations in such cases (e.g. the Triadic Aspect method), but this solves only the user cold start problem and enforces user’s privacy. Some systems use users’ ’stereotypes’ to generate recommendations, but stereotypes often do not reflect the actual preferences of individual users. While some other systems use user’s ’filterbots’ by injecting pseudo users or bots into the system and consider these as existing ones, but this leads to poor accuracy. We propose the active node method, that uses previous and recent users’ browsing targets and browsing patterns to infer preferences and generate recommendations (node recommendations, in which a single suggestion is given, and batch recommendations, in which a set of possible target nodes are shown to the user at once). We compare the active node method with three alternative methods (Triadic Aspect Method, Naïve Filterbots Method, and MediaScout Stereotype Method), and we used a dataset collected from online web news to generate recommendations based on our method and based on the three alternative methods. We calculated the levels of novelty, coverage, and precision in these experiments, and we found that our method achieves higher levels of novelty in batch recommendation while achieving higher levels of coverage and precision in node recommendations comparing to these alternative methods. Further, we develop a variant of the active node method that incorporates semantic structure elements. A further experimental evaluation with real data and users showed that semantic node recommendation with the active node method achieved higher levels of novelty than nonsemantic node recommendation, and semantic-batch recommendation achieved higher levels of coverage and precision than non-semantic batch recommendation

    Implementing 5D BIM on construction projects: Contractor perspectives from the UK construction sector

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    This is an accepted manuscript of an article published by Emerald in Journal of Engineering, Design and Technology on 09/05/2020: https://doi.org/10.1108/JEDT-01-2020-0007 The accepted version of the publication may differ from the final published version.Purpose The purpose of this paper is to report on primary research findings that sought to investigate and analyse salient issues on the implementation of 5D building information modelling (BIM) from the UK contractors’ perspective. Previous research and efforts have predominantly focussed on the use of technologies for cost estimation and quantity takeoff within a more traditional-led procurement, with a paucity of research focussing on how 5D BIM could facilitate costing within contractor-led procurement. This study fills this current knowledge gap and enhances the understanding of the specific costing challenges faced by contractors in contractor-led projects, leading to the development of 5D framework for use in future projects. Design/methodology/approach To develop a fully detailed understanding of the challenges and issues being faced in this regard, a phenomenological, qualitative-based study was undertaken through interviews involving 21 participants from UK-wide construction organisations. A thematic data analytical process was applied to the data to derive key issues, and this was then used to inform the development of a 5D-BIM costing framework. Findings Multi-disciplinary findings reveal a range of issues faced by contractors when implementing 5D BIM. These exist at strategic, operational and technological levels which require addressing successful implementation of 5D BIM on contractor-led projects adhering to Level 2 BIM standards. These findings cut across the range of stakeholders on contractor-led projects. Ultimately, the findings suggest strong commitment and leadership from organisational management are required to facilitate cost savings and generate accurate cost information. Practical implications This study highlights key issues for any party seeking to effectively deploy 5D BIM on a contractor-led construction project. A considerable cultural shift towards automating and digitising cost functions virtually, stronger collaborative working relationship relative to costing in design development, construction practice, maintenance and operation is required. Originality/value By analysing findings from primary research data, the work concludes with the development of a 5D BIM costing framework to support contractor-led projects which can be implemented to ensure that 5D BIM is successfully implemented

    Knowledge Representation with Ontologies: The Present and Future

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    Recently, we have seen an explosion of interest in ontologies as artifacts to represent human knowledge and as critical components in knowledge management, the semantic Web, business-to-business applications, and several other application areas. Various research communities commonly assume that ontologies are the appropriate modeling structure for representing knowledge. However, little discussion has occurred regarding the actual range of knowledge an ontology can successfully represent

    The future of technology enhanced active learning – a roadmap

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    The notion of active learning refers to the active involvement of learner in the learning process, capturing ideas of learning-by-doing and the fact that active participation and knowledge construction leads to deeper and more sustained learning. Interactivity, in particular learnercontent interaction, is a central aspect of technology-enhanced active learning. In this roadmap, the pedagogical background is discussed, the essential dimensions of technology-enhanced active learning systems are outlined and the factors that are expected to influence these systems currently and in the future are identified. A central aim is to address this promising field from a best practices perspective, clarifying central issues and formulating an agenda for future developments in the form of a roadmap

    Learning and Activity Patterns in OSS Communities and their Impact on Software Quality

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    This paper presents a framework to identify and analyse learning and activity patterns that characterise participation and collaboration of individuals in Open Source Software (OSS) communities.  It first describes how participants’ activities enable and drive a learning process that occurs in individual participants as well as in the OSS project community as a whole. It then explores how to identify and analyse learning patterns at both individual level and community level. The objective of such analysis is to determine the impact of these patterns on the quality of the OSS product and define a descriptive approach to quality that is concerned less with standards than with the facts of OSS peer-review and peer-production
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