Construction of university ontology

Ameen, Ayesha; Khan, Khaleel Ur Rahman; Rani, B. Padmaia

doi:10.1109/wict.2012.6409047

Cited by 15 publications

(6 citation statements)

References 3 publications

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“…Finally, the OWLViz Protégé plugin has been used to visualize the ontology structure and to provide the whole picture of all relations among the classes. Another ontology for the university was developed in [12]. In this work, the main focus of the authors was on building university ontology methods using protégé 4.0.…”

Section: Related Workmentioning

confidence: 99%

Ontology-Based Smart System to Automate Higher Education Activities

et al. 2021

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The need for smart e-learning environments is resulting in new challenges for researchers and practitioners to develop intelligent systems that can be used to automate the Higher Education (HE) activities in an intelligent way. Some common examples of such activities are “analyzing, finding, and ranking the right resource to teach a course,” “analyzing and finding the people with common research interests to start joint research projects,” and “using data analytics and machine reasoning techniques for conducting the exams with different levels of complexities.” Ontological reasoning and smart data analytics can play an important role in analyzing and automating these HE activities and processes. In this paper, we present a framework named as Higher Education Activities and Processes Automation Framework (HEAPAF). The HEAPAF framework can be used to identify, extract, process, and produce the semantically enriched data in machine understandable format from different educational resources. We also present the Higher Education Ontology (HEO) that we designed and developed to accommodate the HE data and then to perform analysis and reasoning on it. As a proof of concept, we present a case study on the topic, “analyzing, finding, and ranking the right resources to teach a course,” which can dramatically improve the learning patterns of students in the growing smart educational environment. Finally, we provide the evaluation of our framework as evidence of its competency and consistency in improving academic analytics for educational activities and processes by using machine reasoning.

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Section: Related Workmentioning

confidence: 99%

Ontology-Based Smart System to Automate Higher Education Activities

et al. 2021

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“…where the knowledge about locations, persons, or activities is mainly concerned. Ontologies about indoor spaces, people, activities can be found in literatures [26][27][28][29], and Protégé ontology library 1 can also be used as a good reference. We chose to design the ontology ourselves because of the specificity of the application.…”

Section: Construction Of the Domain Knowledge Ontologymentioning

confidence: 99%

Information Retrieval Based on Knowledge-Enhanced Word Embedding Through Dialog: A Case Study

Ren¹,

Wang²,

Liu³

2020

IJCIS

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The aim of this paper is to provide a systematic route of information retrieval from a knowledge-based database (or domain knowledge) through a dialog system of natural language interaction. The application is about a comprehensive building at a university, with classrooms, laboratory rooms, meeting rooms, research rooms and offices, and is to present related information the user asks for. First, the domain knowledge is expressed with predicate expressions based on the ontology structure; then the vocabulary is presented distributedly with word embedding enhanced with the domain knowledge; queries from the user are then converted into the intent (general) and slot elements (specific) with the help of trained recurrent neural network (RNN). The system works smoothly. The key point is integrating the two methods of knowledge-based and data-driven natural language processing into one system, and the domain knowledge is in the central part which is incorporated into the word embedding to make it specifically fit the natural language in this application.

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“…Data properties specify relationships between individuals (or instances) and data values [108]. Therefore, for the class 'seizure type' has a certain name or code, or 'patient' has "profile ID".…”

Section: B14 Define the 'Object Properties' 'Data Properties' And 'In...mentioning

confidence: 99%

An IoT Approach to Personalised Remote Monitoring and Management of Epilepsy

Mchale

Pereira

Weishmann

et al. 2017

2017 14th International Symposium on Pervasive Systems, Algorithms and Networks &Amp; 2017 11th International Conference on Fro

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I am grateful to the individuals that participated in the clinical studies described in this thesis. I would like to thank them for their patience, generosity, and courage. Thanks to Dr. Udo Weishmann his mentorship and input while I carried out this project; our initial fortuitous meeting was to make-way for this influential collaboration. Thanks, Udo, for sharing the passion to help epilepsy patients which has motivated us throughout. Thanks to Becky Higginbottom and Amy Ibbotson, and all the Clinical Physiologists' at the Walton Centre for assisting me with patient profile collection and teaching me valuable epilepsy terminology and the methods at the Neurophysiology Department.Thanks to the NRES committee London-Dulwich (HEALTH RESEARCH AUTHORITY) for supporting me in the design of clinical studies, and for helping me with the NHS IRAS (Integrated Research Approval System). Thanks to Dave Watling for making the ethical aspects of the studies at The Walton Centre possible. The App system used in these studies could not have been built without the help of my colleague and fellow PhD researcher Oladotun Omosebi: his determination, positivity and skill will long live in the memory. I am hugely thankful for the input from my supervisory team; Professor

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Construction of university ontology

Cited by 15 publications

References 3 publications

Ontology-Based Smart System to Automate Higher Education Activities

Ontology-Based Smart System to Automate Higher Education Activities

Information Retrieval Based on Knowledge-Enhanced Word Embedding Through Dialog: A Case Study

An IoT Approach to Personalised Remote Monitoring and Management of Epilepsy

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