Outbound logistics exception monitoring: A multi-perspective ontologies’ approach with intelligent agents

Xu, Dongming; Wijesooriya, Chinthake; Wang, Yonggui; Beydoun, Ghassan

doi:10.1016/j.eswa.2011.04.111

Cited by 12 publications

(15 citation statements)

References 23 publications

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“…Applying a model driven approach to share DM knowledge has the added benefit of also making knowledge accessible to non-technical specialists and newcomers to DM (Lauras et al 2015;Xu et al 2011). Similar to modeldriven software development, this also requires a DM modelling language to specify all elements with which any model can be described.…”

Section: Background and Related Workmentioning

confidence: 99%

A metamodel-based knowledge sharing system for disaster management

Othman

Beydoun

2016

Expert Systems with Applications

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Section: Background and Related Workmentioning

confidence: 99%

A metamodel-based knowledge sharing system for disaster management

Othman

Beydoun

2016

Expert Systems with Applications

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“…Several authors propose learning path graph [14,22,26], concept map [30], and ontology [18,31]. Specifically, the use of graph theory is not new in e-learning, however, there has been no formal model for discussing learning path problems based on graph theory.…”

Section: Approaches To Learning Path Problemmentioning

confidence: 99%

Learning path adaptation in online learning systems

Muhammad

Zhou

Beydoun

et al. 2016

2016 IEEE 20th International Conference on Computer Supported Cooperative Work in Design (CSCWD)

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Learning path in online learning systems refers to a sequence of learning objects which are designated to help the students in improving their knowledge or skill in particular subjects or degree courses. In this paper, we review the recent research on learning path adaptation to pursue two goals, first is to organize and analyze the parameter of adaptation in learning path; the second is to discuss the challenges in implementing learning path adaptation. The survey covers the state of the art and aims at providing a comprehensive introduction to the learning path adaptation for researchers and practitioners. Abstract-Learning path in online learning systems refers to a sequence of learning objects which are designated to help the students in improving their knowledge or skill in particular subjects or degree courses. In this paper, we review the recent research on learning path adaptation to pursue two goals, first is to organize and analyze the parameter of adaptation in learning path; the second is to discuss the challenges in implementing learning path adaptation. The survey covers the state of the art and aims at providing a comprehensive introduction to the learning path adaptation for researchers and practitioners.

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“…For the pattern level, the ontologies are constructed based on conceptual graphs, as we briefly described in Section 3.1.1. By this means, the ontologies represent the formal dimensions of the data processing workflow, and can drive data processing with a priori knowledge, thereby reducing the search space [23,31].…”

Section: Conceptual Graph-based Ontology Constructionmentioning

confidence: 99%

“…Given that we have the overall system framework in place, we consequently adopt a conceptual graph-based approach for dealing with the ontology construction [22,23]. These graphs profile the features that play a significant role in an ongoing micro learning process, and also depict how features were mutually affected by and interrelated with each other.…”

Section: Research Problem Identification and Designmentioning

confidence: 99%

Towards Massive Data and Sparse Data in Adaptive Micro Open Educational Resource Recommendation: A Study on Semantic Knowledge Base Construction and Cold Start Problem

et al. 2017

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Abstract:Micro Learning through open educational resources (OERs) is becoming increasingly popular. However, adaptive micro learning support remains inadequate by current OER platforms. To address this, our smart system, Micro Learning as a Service (MLaaS), aims to deliver personalized OER with micro learning to satisfy their real-time needs. In this paper, we focus on constructing a knowledge base to support the decision-making process of MLaaS. MLaas is built using a top-down approach. A conceptual graph-based ontology construction is first developed. An educational data mining and learning analytic strategy is then proposed for the data level. The learning resource adaptation still requires learners' historical information. To compensate for the absence of this information initially (aka 'cold start'), we set up a predictive ontology-based mechanism. As the first resource is delivered to the beginning of a learner's learning journey, the micro OER recommendation is also optimized using a tailored heuristic.

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Outbound logistics exception monitoring: A multi-perspective ontologies’ approach with intelligent agents

Cited by 12 publications

References 23 publications

A metamodel-based knowledge sharing system for disaster management

A metamodel-based knowledge sharing system for disaster management

Learning path adaptation in online learning systems

Towards Massive Data and Sparse Data in Adaptive Micro Open Educational Resource Recommendation: A Study on Semantic Knowledge Base Construction and Cold Start Problem

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