Relevant bibliographies by topics / Ontology-Learning Methodology

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Ontology-Learning Methodology'

Author: Grafiati
Published: 4 June 2025
Last updated: 23 June 2025

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Journal articles on the topic "Ontology-Learning Methodology"

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Taye, Mohammad Mustafa. "Enhanced Agile Methodology for Ontology Development in E-Learning Environments." International Journal of Interactive Mobile Technologies (iJIM) 18, no. 16 (2024): 4–24. http://dx.doi.org/10.3991/ijim.v18i16.49225.

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This study explores the use of agile approaches to the creation of ontologies for e-learning, evaluating the benefits and drawbacks as well as the impact on information display. Traditional strategies conflict with the need to fulfill the ever-evolving expectations of users and adapt to the ever-changing features of e-learning environments. The challenge aims to encourage cooperation and versatility in the creation of ontologies for e-learning through the use of Agile standards. Because they make it simpler to organize relationships and statistics, ontologies are vital elements in e-mastering domain names due to the fact that they permit adaptive knowledge of structures and individualized learning experiences. Agile ontology engineering approaches are proposed as a choice for one’s problems, emphasizing flexibility and response. This study highlights the need to work together with customers and incorporate their input into the advent of ontologies. It notably emphasizes using established feedback loops and cooperation with e-learning platform companies. The sensible usefulness and effectiveness of agile methodology for ontology development (AMOD) in e-learning settings are shown through validation efforts in real-global conditions.
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Gil, Richard, and Maria J. Martin-Bautista. "SMOL: a systemic methodology for ontology learning from heterogeneous sources." Journal of Intelligent Information Systems 42, no. 3 (2014): 415–55. http://dx.doi.org/10.1007/s10844-013-0296-x.

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El Idrissi Esserhrouchni, Omar, Bouchra Frikh, Brahim Ouhbi, and Ismail Khalil Ibrahim. "Learning domain taxonomies: the TaxoLine approach." International Journal of Web Information Systems 13, no. 3 (2017): 281–301. http://dx.doi.org/10.1108/ijwis-04-2017-0024.

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Purpose The aim of this paper is to present an online framework for building a domain taxonomy, called TaxoLine, from Web documents automatically. Design/methodology/approach TaxoLine proposes an innovative methodology that combines frequency and conditional mutual information to improve the quality of the domain taxonomy. The system also includes a set of mechanisms that improve the execution time needed to build the ontology. Findings The performance of the TaxoLine framework was applied to nine different financial corpora. The generated taxonomies are evaluated against a gold-standard ontology and are compared to state-of-the-art ontology learning methods. Originality/value The experimental results show that TaxoLine produces high precision and recall for both concept and relation extraction than well-known ontology learning algorithms. Furthermore, it also shows promising results in terms of execution time needed to build the domain taxonomy.
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Valaski, Joselaine, Sheila Reinehr, and Andreia Malucelli. "An ontology to support the classification of learning material in an organizational learning environment." Interactive Technology and Smart Education 14, no. 1 (2017): 67–87. http://dx.doi.org/10.1108/itse-11-2016-0044.

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Purpose The purpose of this research was to evaluate whether ontology integrated in an organizational learning environment may support the automatic learning material classification in a specific knowledge area. Design/methodology/approach An ontology for recommending learning material was integrated in the organizational learning environment based on ontology. An experiment was performed with 15 experts and 84 learners. Experts and learners were asked to classify 30 learning material related to Software Engineering area. The results obtained from experts and learners were compared with the ontology results. Findings Among 30 learning materials evaluated, 24 learning materials got closer to the expert classification using the ontology than using the learners’ manual classification. The learners had difficulties in correctly classifying the learning materials according to the knowledge area applied. Originality/value In an autonomous collaborative environment without a tutor responsible for organizing the learning materials shared by collaborators, an ontology may be an auxiliary mechanism to support automatic learning material classification. The proposed ontology uses recommendations given by the collaborators to get the correct knowledge area classification. The correct classification may support retrieval of appropriate learning materials according to the learners’ needs.
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Sathiya, B., and T. V. Geetha. "Automatic Ontology Learning from Multiple Knowledge Sources of Text." International Journal of Intelligent Information Technologies 14, no. 2 (2018): 1–21. http://dx.doi.org/10.4018/ijiit.2018040101.

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The prime textual sources used for ontology learning are a domain corpus and dynamic large text from web pages. The first source is limited and possibly outdated, while the second is uncertain. To overcome these shortcomings, a novel ontology learning methodology is proposed to utilize the different sources of text such as a corpus, web pages and the massive probabilistic knowledge base, Probase, for an effective automated construction of ontology. Specifically, to discover taxonomical relations among the concept of the ontology, a new web page based two-level semantic query formation methodology using the lexical syntactic patterns (LSP) and a novel scoring measure: Fitness built on Probase are proposed. Also, a syntactic and statistical measure called COS (Co-occurrence Strength) scoring, and Domain and Range-NTRD (Non-Taxonomical Relation Discovery) algorithms are proposed to accurately identify non-taxonomical relations(NTR) among concepts, using evidence from the corpus and web pages.
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Rahmani, Mahdi, and Beheshti Moluksadat Hosseini. "Designing an E-Learning System Based on Ontology." Journal of Information Processing and Management 36, no. 1 (2020): 271–94. https://doi.org/10.5281/zenodo.14039589.

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The aim of the present research is to design an e-learning system based on ontology. This study is applied in nature and is classified as descriptive research. In this research, the main concepts in the field of e-learning were extracted by reviewing published articles and information resources related to e-learning. Ultimately, the main categories in the field of e-learning were identified, including human resources, technological infrastructure, and educational content. The methodology used for extracting concepts and semantic relationships was based on knowledge engineering, while the method employed for creating the ontology was a top-down approach. Additionally, the software "Protégé" version 5.3 was used to construct the ontology. The research followed seven stages for ontology construction, which included determining the scope and coverage of the ontology, establishing the hierarchy of the ontology, identifying conceptual pairs, defining categories, describing features, defining instances, and creating examples. Based on the research findings, the proposed method can be utilized to complete and develop the suggested ontology in the field of e-learning.
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Ekwealor, Oluchukwu, Chidi Betrand, Chiemeka Chukwudum, Charles Uchefuna, and Obinna Agbata. "Development of a Semantic Web-Ontology E-Learning Platform." American Journal of Computer Science and Technology 7, no. 4 (2024): 176–82. http://dx.doi.org/10.11648/j.ajcst.20240704.15.

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This paper is focused on developing A Semantic Web-Ontology E-Learning Platform, which is a system that combines semantic web and ontology technology to guarantees a sophisticated learning environment that provides the learners with adaptable and customized learning resources based on learners’ knowledge requirement. With this system, learners can log in from their comfort zone anytime, to receive their online lesson as provided by their tutor. The system has an added advantage of providing a personalized learning to students through creation of intelligent search engine and ontology backbone consisting of learning data and their meta data. The learner, through this search engine, searches the ontology semantically for the learning materials that suits his/her profile. The system also has the capability of filtering the search results by matching them with the profile of a particular learner using inference engine, such that the result best suited for the user’s academic need is presented. This work will not only promote self-directed learning but will also facilitate quick search of learning materials, by narrowing the search based on specified learner’s interest. The methodology adopted for this work is Object-Oriented Analysis and Design Methodology (OOADM) and programing languages used are Php-Mysql and Java Script. The system will be of great benefit to schools, other learning institutions and organization seeking to educate their manpower.
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Zhou, Yang, Zhao Yang Zeng, Bin Tian, Zhi Yu Jia, and Xiao Guo. "Ontology Modeling of Aircraft Fault Knowledge." Applied Mechanics and Materials 236-237 (November 2012): 350–55. http://dx.doi.org/10.4028/www.scientific.net/amm.236-237.350.

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With consideration of the actual requirement of fault knowledge management in current aviation maintenance, ontology-based knowledge representation method of aircraft fault is studied. Knowledge sources of aircraft fault ontology are analyzed based on ontology modeling primitives. Ontology construction method of aircraft fault knowledge is proposed learning from software engineering and the essence of the existing ontology construction methodology. On the basis of the above study, aircraft fault ontology which is consist of Fault Core sub-ontology, Product domain sub-ontology, Case domain sub-ontology, and Diagnosis domain sub-ontology is build, and it represents aircraft fault knowledge completely and consistently, and also lays the foundation for knowledge management of aircraft fault.
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Jacksi, Karwan. "Design and Implementation of E-Campus Ontology with a Hybrid Software Engineering Methodology." Science Journal of University of Zakho 7, no. 3 (2019): 95–100. http://dx.doi.org/10.25271/sjuoz.2019.7.3.613.

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Semantic Web according to the vision of the W3C is the future of WWW (or Web). It is an extension of the current Web through standards by the W3C. Data of the Semantic Web has well-defined meanings, can be understood by devices and allows machines and people to work in collaboration. Ontologies are vital components of the Semantic Web infrastructure and are more often recognized as the backbone of the Semantic Web. Although numerous developments occur in the field of developing ontologies along the lines with the Semantic Web implementation, but standardizing the process models, tools and methodologies need to be improved in the future. In literature, experts in ontology engineering have stated that setting a methodology for developing ontology applications with support of integrated tools is an essential task for ontology engineering to be succeeded. In this paper, an e-campus ontology for educational purposes is designed and implemented, and mainly focused on the learning hierarchy of C-sharp programming language. A hybrid methodology based on software engineering approaches for developing ontologies is presented. Finally, the developed methodology is applied on the implemented ontology.
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Kero, ADMAS, Dawit Demissie, and Kula Kekeba. "Leveraging Ontology-Driven Machine Learning for Public Policy Analysis: A Systematic Review of Social Media Applications." IJID (International Journal on Informatics for Development) 13, no. 2 (2024): 485–503. https://doi.org/10.14421/ijid.2024.4176.

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As social media platforms increasingly serve, machine learning techniques are formulated with particular ontologies, which furnish invaluable resources. This qualitative literature review investigates the incorporation of ontology-driven machine learning methodologies for analysing public policy utilizing social media data. This review encompasses findings from scholarly research published between 2019 and 2024 that apply ontologies to enhance models' interpretation, precision, and flexibility across diverse sectors, including health, environment, economy, and culture. An integrated methodology is adopted to identify, select, and evaluate pertinent studies by scrutinizing elements such as genre ontology, machine learning, existing literature, and evaluation metrics. The findings indicate that the ontology-centric framework facilitates the extraction process and semantic analysis, ultimately contributing to a more nuanced comprehension of unstructured data. Nonetheless, obstacles persist in ontology development concerning capacity enhancement, data integrity, and ethical considerations. The review concludes with a discourse on the ramifications for policymakers and researchers who may leverage these insights to guide decision-making, and scholars are now urged to confront limitations and investigate novel platforms, metrics, and ethical frameworks. The review underscores the potential of ontology-driven machine learning as a formidable strategy in the advancement of policy research and social analysis.
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Dissertations / Theses on the topic "Ontology-Learning Methodology"

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Bathija, Vishal. "An Adaptation Methodology for Reusing Ontologies." Miami University / OhioLINK, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=miami1155673377.

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Simmonds, Shan Robyn. "Primary school learners' understanding of human rights teaching-and-learning in classroom practice / S.R. Simmonds." Thesis, North-West University, 2010. http://hdl.handle.net/10394/6257.

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The National Curriculum Statement (2002), in line with the South African Constitution (1996), views human rights, inclusivity and social justice as priorities in all learning areas of the curriculum. However, a document such as the Manifesto on Values, Education and Democracy (2001) illustrates the complexities of addressing this in practice. One of the reasons is that there are misconceptions about how the concept of 'human rights' should be interpreted in the educational realm. This study sets out to explore how primary school learners understand human rights teaching-and-learning (from a moral and value stance) and what factors influence this. The intention is to rethink and redefine human rights teaching-and-learning from a learner's perspective as well as to investigate the notion that regards human rights as 'misunderstood'. This research offers a new perspective on human rights in that it focuses on primary school learners. Therefore this study will provide another lens through which to consider human rights teaching-and-learning in classroom practice. A literature study and empirical research have been undertaken to investigate how learners understand human rights teaching-and-learning. The literature study explores ontological, epistemological and methodological perspectives of human rights teaching-and-learning. Qualitative observation, written narratives and focus-group interviews formed the bases of this empirical research. Ongoing triangulation is used to ensure that the research findings are valid and trustworthy. It seems that primary school learners do have an understanding of human rights teaching-and-learning, which is characterized by an emphasis on legal rights and the contextualisation of human rights within South African, value and educational contexts. Educational and societal factors are two of the factors that influence this understanding. It is clear that learners' understanding of human rights teaching-and-learning is not one-dimensional. However, there are certain ontological ambiguities in the views that learners hold of the significance of human rights teaching-and-learning -both within and beyond the curriculum. An indication of this is that learners' responses reveal that they are often uncertain about why they have to learn about human rights and the contexts and/or learning areas (other than Life Orientation) in which human rights teaching-and-learning should take place. Recommendations highlight the need to gain a better understanding of classroom practices so that teaching-and-learning can infuse a culture of human rights; to acknowledge that human rights teaching-and-learning should be more flexible; to use an implicit way of generating an understanding of human rights; to make human rights teaching and learning in classroom practice more authentic; and to consider 'a human rights beyond the curriculum approach'. This study also identifies areas in which further research should be done.<br>Thesis (M.Ed.)--North-West University, Potchefstroom Campus, 2010.
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Books on the topic "Ontology-Learning Methodology"

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Guy, Merchant, ed. Web 2.0 for schools: Learning and social participation. Peter Lang, 2009.

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Book chapters on the topic "Ontology-Learning Methodology"

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Ivanova, Tatyana, Rumen Andreev, and Valentina Terzieva. "Integration of Ontology with Development of Personalized E-Learning Facilities for Dyslexics." In Artificial Intelligence: Methodology, Systems, and Applications. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15431-7_29.

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El Idrissi, Bouchra, Salah Baïna, and Karim Baïna. "A Methodology to Prepare Real-World and Large Databases to Ontology Learning." In Enterprise Interoperability VI. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04948-9_15.

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Damonte, Alessia, and Fedra Negri. "Conclusions. Causality Between Plurality and Unity." In Texts in Quantitative Political Analysis. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-12982-7_11.

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AbstractThe previous chapters convey the image of causal analysis in public policy and beyond as a fragmented field where research communities seldom learn from each other’s findings. This chapter resumes the ontological, epistemological, and methodological evidence that causal analysis is characterized by a plurality of objects and “incommensurable” interpretations. It also argues that the same evidence pinpoints how this plurality is complementary at every level, and causal structures raise as the elements that link ontology and methodology and can organize heterogeneous findings to improve learning across accounts.
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Lenci Alessandro, Montemagni Simonetta, Pirrelli Vito, and Venturi Giulia. "Ontology learning from Italian legal texts." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2009. https://doi.org/10.3233/978-1-58603-942-4-75.

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The paper reports on the methodology and preliminary results of a case study in automatically extracting ontological knowledge from Italian legislative texts. We use a fully&amp;ndash;implemented ontology learning system (T2K) that includes a battery of tools for Natural Language Processing (NLP), statistical text analysis and machine language learning. Tools are dynamically integrated to provide an incremental representation of the content of vast repositories of unstructured documents. Evaluated results, however preliminary, show the great potential of NLP&amp;ndash;powered incremental systems like T2K for accurate large&amp;ndash;scale semi&amp;ndash;automatic extraction of legal ontologies.
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Draganidis, Fotis, and Gregoris Mentzas. "Ontology-Based Competency Management for Corporate E-Learning." In Competencies in Organizational E-Learning. IGI Global, 2007. http://dx.doi.org/10.4018/978-1-59904-343-2.ch015.

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The synergies between ontology management, competency management and e-learning have been explored during the last years both in theoretical and practical level. This chapter describes the architecture, design and deployment of a system which integrates ontologies, with competency management and e-learning, as well as with other human resources functions. Moreover, a detailed description of the supportive methodology and the main lessons learned in technical and organisational areas are presented. This system is being currently deployed for research purposes in a national subsidiary of Microsoft, the IT services multinational firm. The objective of this chapter is to provide the reader with an overview of the key concepts in competency based management, a non-technical methodology for supporting the effective deployment of an ontology-based competency management system and an analysis of the lessons learned during the first deployment phase.
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S., Pakkir Mohideen. "Personalized Ontology-Based Adaptive E-Learning System." In Machine Learning Approaches for Improvising Modern Learning Systems. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-5009-0.ch002.

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This chapter illustrates novel methods to provide personalized and adaptive content to the learners. This chapter illustrates a new methodology of automatically constructing concept maps using ontology to measure the learners' understanding for a particular topic, thereby teachers can adopt adaptive teaching based on the learners knowledge structures as reflected in the concept maps. The teachers can dynamically revise and deliver instructional materials according to the learners' current progress. In the approach, the authors provide dynamic content to the learners based on neuro fuzzy domain ontology extraction algorithm. This method also provides a personalized ontology model of a learner to learn the ontological user profiles from both world knowledge base and user local instance repositories. The main quality of the innovative work is to mine the personalized ontology of the learners to extract their knowledge through ontology mining using Inc Span+ algorithm.
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Gavrilova Tatiana, Gorovoy Vladimir, and Bolotnikova Ekaterina. "New Ergonomic Metrics for Educational Ontology Design and Evaluation." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2012. https://doi.org/10.3233/978-1-61499-125-0-361.

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This article presents an approach aimed at creating teaching strategies for e-learning based on the principles of ontological engineering and cognitive psychology. For the last ten years visual representation of knowledge has been topical in e-learning methodology and it is heavily connected to ontology design and development. The proposed framework is aimed to develop a methodology where the design of ontology is evaluated by assessing its structure with several quantitative metrics. This can scaffold the process of knowledge structuring and orchestrating teaching ontologies for courseware design. The refining procedure is essential for ontology design and development. Illustrative domain ontologies are helpful in learning process. The main idea is to use visual techniques of mind-mapping and concept mapping as a powerful learning tool. Cognitive bias and some results of Gestalt psychology form a general guideline. The ideas of balance, clarity, and beauty are applied to the ontology evaluation procedures. Such approach can be widely used in enterprise knowledge management systems, in education processes, and can help educators and students create ontologies of high quality.
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Karen, Stauffer, Fuhua Lin, and Koole Marguerite. "A Methodology for Developing Learning Objects for Web Course Delivery." In Advances in Distance Education Technologies. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-60566-934-2.ch019.

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This article presents a methodology for developing learning objects for web-based courses using the IMS Learning Design (IMS LD) specification. We first investigated the IMS LD specification, determining how to use it with online courses and the student delivery model, and then applied this to a Unit of Learning (UOL) for online computer science courses. We developed an editor and runtime environment to apply the IMS LD to a UOL. We then explored the prospect for advancement of the basic IMS LD UOL. Finally, we discussed how to construct ontology-based software agents to use with the learning objects created with the IMS LD Units of Learning.
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Sankat, Monica, R. S. Thakur, and Shailesh Jaloree. "Semi-Automatic Ontology Design for Educational Purposes." In Pattern and Data Analysis in Healthcare Settings. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-0536-5.ch007.

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In this paper, we present a (semi) automatic framework that aims to produce a domain concept from text and to derive domain ontology from this concept. This paper details the steps that transform textual resources (and particularly textual learning objects) into a domain concept and explains how this abstract structure is transformed into more formal domain ontology. This methodology targets particularly the educational field because of the need of such structures (Ontologies and Knowledge Management). The paper also shows how these structures make it possible to bridge the gap between core concepts and Formal ontology.
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Deng, Lawrence Y., Huan-Chao Keh, and Yi-Jen Liu. "Ontology-Based Multimedia Authoring Tool for Adaptive E-Learning." In Intelligent Learning Systems and Advancements in Computer-Aided Instruction. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-61350-483-3.ch008.

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More video streaming technologies supporting distance learning systems are becoming popular among distributed network environments. In this paper, the authors develop a multimedia authoring tool for adaptive e-learning by using characterization of extended media streaming technologies. The distributed approach is based on an ontology-based model. Suppose a well-known teacher is giving a lecture/presentation to his student. Because of time constraints and other commitments, many students cannot attend. The main goal of the authors’ system is to provide a feasible method to record and represent a lecture/presentation using a browser with the windows media services. This system requires flexible support for the modeling of multimedia content models and supports possible interactivity, transfer of streams multimedia data such as audio, video, text, and annotations using network facilities. The authors propose a new approach for the modeling of reusable and adaptable multimedia content. A comprehensive system for advanced multimedia content production is also developed. This approach significantly impacts and supports the multimedia presentation authoring processes in terms of methodology and commercial aspects.
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Conference papers on the topic "Ontology-Learning Methodology"

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Niculescu, Cristina, and Angela Ionita. "ONTOLOGY ENGINEERING AND E-LEARNING SYSTEMS." In eLSE 2015. Carol I National Defence University Publishing House, 2015. http://dx.doi.org/10.12753/2066-026x-15-052.

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Ontology Engineering and E-learning Systems by Cristina NICULESCU and Angela IONI?? Ontology engineering has become an effective methodology for knowledge representation and management in many fields of information science, such as cooperative information systems, intelligent integration of information extraction and information retrieval, knowledge representation systems, database management systems and e-learning systems. It allows being a bridge between human knowledge and knowledge bases. Ontology engineering covers a range of activities that are performed during the conceptualization, design, implementation and development of ontologies. Ontologies in intelligent educational systems can be approached from several points of view: as a common vocabulary for a multi-agent system, as a chain of different heterogeneous educational systems, ontologies for sharing pedagogical resources, or for sharing data and ontologies used in search mediation on the Internet of learning materials. Ontologies can be used to model educational domains and to build, organize and update specific learning resources: learning objects, learner profiles, learning paths, etc. One of our use cases concerns a system that uses structured descriptions of measuring instruments existent in an academic laboratory, for generating Web pages with guidelines regarding students' practical work. The combination between a general learning ontology and one specific to the studied domain can leverage students' capability to understand the new lessons, and create the habit to rigorously use the dedicated taxonomy and to perceive the relationships between concepts. The other use case aims to implement an ontology for personalized e-learning environment that facilitates the sharing and reuse of e-learning materials. ADL SCORM v1.3 application profile was selected to describe the metadata of digital learning materials.
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Sharma, Monika, Supriya Lamba Sahdev, Gurinder Singh, and Bhawna Kumar. "Methodology for the Development of an Ontology based E-Learning Platform." In 2020 International Conference on Computation, Automation and Knowledge Management (ICCAKM). IEEE, 2020. http://dx.doi.org/10.1109/iccakm46823.2020.9051540.

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"A SYSTEMIC METHODOLOGY FOR ONTOLOGY LEARNING - An Academic Case Study and Evaluation." In International Conference on Knowledge Engineering and Ontology Development. SciTePress - Science and and Technology Publications, 2010. http://dx.doi.org/10.5220/0003070602060212.

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Gil, Richard, Maria J. Martin-Bautista, and Leonardo Contreras. "Applying an Ontology Learning Methodology to a Relational Database: University Case Study." In 2010 IEEE Fourth International Conference on Semantic Computing (ICSC). IEEE, 2010. http://dx.doi.org/10.1109/icsc.2010.46.

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Cujar-Rosero, Felipe, David Santiago Pinchao Ortiz, Silvio Ricardo Timaran Pereira, and Jimmy Mateo Guerrero Restrepo. "Fenix: A Semantic Search Engine Based on an Ontology and a Model Trained with Machine Learning to Support Research." In 11th International Conference on Computer Science and Information Technology (CCSIT 2021). AIRCC Publishing Corporation, 2021. http://dx.doi.org/10.5121/csit.2021.110709.

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This paper presents the final results of the research project that aimed to build a Semantic Search Engine that uses an Ontology and a model trained with Machine Learning to support the semantic search of research projects of the System of Research from the University of Nariño. For the construction of FENIX, as this Engine is called, it was used a methodology that includes the stages: appropriation of knowledge, installation and configuration of tools, libraries and technologies, collection, extraction and preparation of research projects, design and development of the Semantic Search Engine. The main results of the work were three: a) the complete construction of the Ontology with classes, object properties (predicates), data properties (attributes) and individuals (instances) in Protegé, SPARQL queries with Apache Jena Fuseki and the respective coding with Owlready2 using Jupyter Notebook with Python within the virtual environment of anaconda; b) the successful training of the model for which Machine Learning algorithms and specifically Natural Language Processing algorithms were used such as: SpaCy, NLTK, Word2vec and Doc2vec, this was also done in Jupyter Notebook with Python within the virtual environment of anaconda and with Elasticsearch; and c) the creation of FENIX managing and unifying the queries for the Ontology and for the Machine Learning model. The tests showed that FENIX was successful in all the searches that were carried out because its results were satisfactory.
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Nanda, Jyotirmaya, Henri J. Thevenot, Timothy W. Simpson, Soundar R. T. Kumara, and Steven B. Shooter. "Exploring Semantic Web Technologies for Product Family Modeling." In ASME 2004 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2004. http://dx.doi.org/10.1115/detc2004-57683.

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By sharing product design information across a family of products, companies can increase the flexibility and responsiveness of their product realization process while shortening lead-times and reducing cost. This paper describes a preliminary attempt at using semantic web paradigm, especially the Web Ontology Language (OWL), for product family information management. An overview of the ongoing work with Semantic Web is also presented. Formal product representation using OWL can not only store the structure of the product family but also help in capturing the evolution of different components of the product family. As an illustration, a group of single-use cameras, containing several products from the Kodak single-use camera family, is represented in OWL format. The methodology of ontology development that can support product family design is discussed in detail. Product family design representation using OWL promotes better learning across products and reduced development time, system complexity, and product design lead-time.
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Elena, RAILEAN. "Problematica managementului tehnologiilor educaționale specifice mediilor de învățare real-virtuale." In "Învățământul superior: tradiţii, valori, perspective", conferinţă ştiinţifică internaţională. Ion Creangă Pedagogical State University, 2022. https://doi.org/10.46727/c.v2.1-2-10-2022.p119-126.

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The global transformation of the school educational system and environment into a diversity of real-virtual learning environments imposes specific conditions on the management of educational theory and technologies. The purpose of this article is to study the issue of knowledge management in a diversity of learning environments. The research methodology is carried out through the met systemic approach of the trends of real-virtual environments in relation to real-virtual learning environments. The results obtained are: a) the permissiveness of real-virtual learning environments is not equivalent to real-virtual environments; b) in pedagogical design and educational management, it is important to respect the ontology norms in relation to the issues of digitization of education. In the conclusions, the importance of studying the ontological component of the educational management has been emphasized.
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Stojanović, Katarina, Božo Ilić, Đorđe Mihailović, Ksenija Orlandić Osmajić, and Radovan Pejanović. "ARTIFICIAL INTELLIGENCE AND DEEP LEARNING ALGORITHMS: A POST-SMART PATH FOR CITIES." In INTERNATIONAL Conference on Business, Management, and Economics Engineering Future-BME. Faculty of Technical Sciences, Novi Sad, 2025. https://doi.org/10.24867/future-bme-2024-122.

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Abstract:
The Artificial intelligence (AI) and deep learning algorithms have had a significant impact in overcoming the concept of a smart city, as evidenced by the latest scientific research. That trajectory is shifting from smart ontology to deep learning algorithms. The work integrates theoretical and practical knowledge of AI cohabitation with the city and how it changes it, but also a reversible process. AI recomposition is also considered, drawing on a number of urban disciplines and case studies. Through a comparative analysis of a series of case studies in cities where different methods of mutual constitutive relations have been applied, a synthesis of conclusions and a series of criteria and recommendations is reached. The chosen methodology is based on the thesis that every local context is unique, and AI system must be developed in a way that is adapted and corresponds to the specific local context. The research reveals the various impacts of AI on society, education, infrastructure, urban planning and sustainable development. The so-called new postsmart path for cities is confirmed through empirical examples and represents a new era and paradigm of future urban life. The urbanism of artificial intelligence was analyzed and the results may be useful in some future research due to the very interdisciplinary nature of the topic both in the fields of urban studies and architecture, as well as from the point of view of studies of scientific and technological development, education, sociology, culture and politics
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