4,681 research outputs found
Improving Knowledge Retrieval in Digital Libraries Applying Intelligent Techniques
Nowadays an enormous quantity of heterogeneous and distributed information is stored in the digital University. Exploring online collections to find knowledge relevant to a userâs interests is a challenging work. The artificial intelligence and Semantic Web provide a common framework that allows knowledge to
be shared and reused in an efficient way. In this work we propose a comprehensive approach for discovering E-learning objects in large digital collections based on analysis of recorded semantic metadata in those objects and the application of expert system technologies. We have used Case Based-Reasoning
methodology to develop a prototype for supporting efficient retrieval knowledge from online repositories.
We suggest a conceptual architecture for a semantic search engine. OntoUS is a collaborative effort that
proposes a new form of interaction between users and digital libraries, where the latter are adapted to users
and their surroundings
Integration of environmental data in BIM tool & linked building data
Environmental assessment is a critical need to ensure building sustainability. In order to enhance the sustainability of building, involved actors should be able to access and share not only information about the building but also data about products and especially their environmental assessment. Among several approaches that have been proposed to achieve that, semantic web technologies stand out from the crowd by their capabilities to share data and enhance interoperability in between the most heterogeneous systems. This paper presents the implementation of a method in which semantic web technologies and particularly Linked Data have been combined with Building Information Modelling (BIM) tools to foster building sustainability by introducing products with their environmental assessment in building data during the modelling phase. Based on Linked Building Data (LBD) vocabularies and environmental data, several ontologies have been generated in order to make both of them available as Resource Description Framework (RDF) graphs. A database access plugin has been developed and installed in a BIM tool. In that way, the LBD generated from the BIM tool contains, for each product a reference to its environmental assessment which is contained in a triplestore
Towards engineering ontologies for cognitive profiling of agents on the semantic web
Research shows that most agent-based collaborations
suffer from lack of flexibility. This is due to the fact that
most agent-based applications assume pre-defined
knowledge of agentsâ capabilities and/or neglect basic
cognitive and interactional requirements in multi-agent
collaboration. The highlight of this paper is that it brings
cognitive models (inspired from cognitive sciences and HCI)
proposing architectural and knowledge-based requirements
for agents to structure ontological models for cognitive
profiling in order to increase cognitive awareness between
themselves, which in turn promotes flexibility, reusability
and predictability of agent behavior; thus contributing
towards minimizing cognitive overload incurred on humans.
The semantic web is used as an action mediating space,
where shared knowledge base in the form of ontological
models provides affordances for improving cognitive
awareness
Past, present and future of information and knowledge sharing in the construction industry: Towards semantic service-based e-construction
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
Continuous Improvement Through Knowledge-Guided Analysis in Experience Feedback
Continuous improvement in industrial processes is increasingly a key element of competitiveness for industrial systems. The management of experience feedback in this framework is designed to build, analyze and facilitate the knowledge sharing among problem solving practitioners of an organization in order to improve processes and products achievement. During Problem Solving Processes, the intellectual investment of experts is often considerable and the opportunities for expert knowledge exploitation are numerous: decision making, problem solving under uncertainty, and expert configuration. In this paper, our contribution relates to the structuring of a cognitive experience feedback framework, which allows a flexible exploitation of expert knowledge during Problem Solving Processes and a reuse such collected experience. To that purpose, the proposed approach uses the general principles of root cause analysis for identifying the root causes of problems or events, the conceptual graphs formalism for the semantic conceptualization of the domain vocabulary and the Transferable Belief Model for the fusion of information from different sources. The underlying formal reasoning mechanisms (logic-based semantics) in conceptual graphs enable intelligent information retrieval for the effective exploitation of lessons learned from past projects. An example will illustrate the application of the proposed approach of experience feedback processes formalization in the transport industry sector
Semantic model-driven development of service-centric software architectures
Service-oriented architecture (SOA) is a recent architectural paradigm that has received much attention. The prevalent focus on platforms such as Web services, however, needs to be complemented by appropriate software engineering methods. We propose the model-driven development of service-centric software systems. We present in particular an investigation into the role of enriched semantic modelling for a modeldriven development framework for service-centric software systems. Ontologies as the foundations of semantic modelling and its enhancement
through architectural pattern modelling are at the core of the proposed approach. We introduce foundations and discuss the benefits and also the challenges in this context
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