Roberto Confalonieri, Oliver Kutz, Diego Calvanese, J. Alonso-Moral, Shang-Ming Zhou
{"title":"本体论和知识在可解释人工智能中的作用","authors":"Roberto Confalonieri, Oliver Kutz, Diego Calvanese, J. Alonso-Moral, Shang-Ming Zhou","doi":"10.3233/sw-243529","DOIUrl":null,"url":null,"abstract":"science. These papers introduced domain-specific ontologies, providing a structured framework to facilitate understanding and explanation of the systems within each domain. The other group of papers took a more foundational approach by presenting logic-based methodologies that fostered the development of explainable-by-design systems. These papers emphasized the use of logical reasoning techniques to achieve explainability and offered frameworks for constructing systems that inherently prioritize interpretability. In summary, the accepted papers demonstrated the utilization of ontologies, knowledge graphs, and knowledge representation and reasoning in advancing the field of XAI. In the following, we provide a broad overview of all the accepted papers.","PeriodicalId":48694,"journal":{"name":"Semantic Web","volume":null,"pages":null},"PeriodicalIF":3.0000,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The role of ontologies and knowledge in Explainable AI\",\"authors\":\"Roberto Confalonieri, Oliver Kutz, Diego Calvanese, J. Alonso-Moral, Shang-Ming Zhou\",\"doi\":\"10.3233/sw-243529\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"science. These papers introduced domain-specific ontologies, providing a structured framework to facilitate understanding and explanation of the systems within each domain. The other group of papers took a more foundational approach by presenting logic-based methodologies that fostered the development of explainable-by-design systems. These papers emphasized the use of logical reasoning techniques to achieve explainability and offered frameworks for constructing systems that inherently prioritize interpretability. In summary, the accepted papers demonstrated the utilization of ontologies, knowledge graphs, and knowledge representation and reasoning in advancing the field of XAI. In the following, we provide a broad overview of all the accepted papers.\",\"PeriodicalId\":48694,\"journal\":{\"name\":\"Semantic Web\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2024-03-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Semantic Web\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.3233/sw-243529\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Semantic Web","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.3233/sw-243529","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
The role of ontologies and knowledge in Explainable AI
science. These papers introduced domain-specific ontologies, providing a structured framework to facilitate understanding and explanation of the systems within each domain. The other group of papers took a more foundational approach by presenting logic-based methodologies that fostered the development of explainable-by-design systems. These papers emphasized the use of logical reasoning techniques to achieve explainability and offered frameworks for constructing systems that inherently prioritize interpretability. In summary, the accepted papers demonstrated the utilization of ontologies, knowledge graphs, and knowledge representation and reasoning in advancing the field of XAI. In the following, we provide a broad overview of all the accepted papers.
Semantic WebCOMPUTER SCIENCE, ARTIFICIAL INTELLIGENCEC-COMPUTER SCIENCE, INFORMATION SYSTEMS
CiteScore
8.30
自引率
6.70%
发文量
68
期刊介绍:
The journal Semantic Web – Interoperability, Usability, Applicability brings together researchers from various fields which share the vision and need for more effective and meaningful ways to share information across agents and services on the future internet and elsewhere. As such, Semantic Web technologies shall support the seamless integration of data, on-the-fly composition and interoperation of Web services, as well as more intuitive search engines. The semantics – or meaning – of information, however, cannot be defined without a context, which makes personalization, trust, and provenance core topics for Semantic Web research. New retrieval paradigms, user interfaces, and visualization techniques have to unleash the power of the Semantic Web and at the same time hide its complexity from the user. Based on this vision, the journal welcomes contributions ranging from theoretical and foundational research over methods and tools to descriptions of concrete ontologies and applications in all areas. We especially welcome papers which add a social, spatial, and temporal dimension to Semantic Web research, as well as application-oriented papers making use of formal semantics.