Ontology based machine learning
Web22 de jun. de 2024 · In this article, selected new directions in knowledge-based artificial intelligence (AI) and machine learning (ML) are presented: ontology development methodologies and tools, automated ...
Ontology based machine learning
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Web23 de abr. de 2024 · Lifelong learning enables professionals to update their skills to face challenges in their changing work environments. In view of the wide range of courses on offer, it is important for professionals to have recommendation systems that can link them to suitable courses. Based on this premise and on our previous research, this paper … Web16 de nov. de 2024 · Applying of Machine Learning Techniques to Combine String-based, Language-based and Structure-based Similarity Measures for Ontology Matching. python machine-learning ontology-matching ontology-alignment oaei. Updated on Apr 23, 2024. Jupyter Notebook.
Web12 de nov. de 2024 · Three tree-based machine learning models were used to classify the neuropathology reports into one or more diagnosis classes with and without ontology ... The epilepsy ontology-based feature engineering approach improved the performance of all the three learning models with an improvement of 35.7%, 54.5%, and 33.3% in ... Web13 de out. de 2024 · This paper describes the creation of an ontology to represent the knowledge around the Machine Learning discipline. Protégé 5 was used, which …
WebHá 1 dia · However, there are few studies directly based on the ferroptosis level obtained by unsupervised clustering and principal component analysis to screen the biomarkers regulating cancer ferroptosis - ferroptosis regulators, especially the lack of effective machine learning screening strategies. Single machine learning algorithm is very … Web26 de set. de 2016 · This paper presents a methodological framework for improving performances of classifying RSOs by harnessing ontology and machine learning …
Web16 de nov. de 2024 · Applying of Machine Learning Techniques to Combine String-based, Language-based and Structure-based Similarity Measures for Ontology Matching. …
WebThis chapter studies ontology matching: the problem of finding the semantic mappings between two given ontologies. This problem lies at the heart of numerous information processing applications. Virtually any application that involves multiple ontologies must establish semantic mappings among them, to ensure interoperability. high density cushionWebOntologies have become an essential component of software pipelines designed to extract, code, and analyze clinical information by machine learning algorithms. The … high density cystWeb13 de mar. de 2024 · Dibley studied the ontology framework for sensor-based building monitoring. In 2016, Zhou and El-Gohary developed an ontology-based text classification algorithm to improve classification performance using the semantics of text. Then in 2024, Zhou and El-Gohary developed an ontology-based information extraction algorithm. high density cushion foam michaelsWeb10 de jan. de 2005 · Bernstein et al. [33] proposed an ontology based intelligent DM to rank the mining process. 3 Bauer and Baldes [34] designed an ontology based interface … how fast does fake news spreadWeb1 de fev. de 2024 · Nevertheless, there are some approaches based only on machine learning techniques to produce ontologies. In the following, we present some … high density curtain wallWeb1 de abr. de 2024 · Ontology-based Interpretable Machine Learning for Textual Data. In this paper, we introduce a novel interpreting framework that learns an interpretable … high density data aqcuisitionWebontology mapping is crucial to the success of the Semantic Web [34]. 2 Overview of Our Solution In response to the challenge of ontology matching on the Semantic Web and in … high density data