{"title":"本体论与数据管理：本体论与数据管理：简要调查。","authors":"Thomas Schneider, Mantas Šimkus","doi":"10.1007/s13218-020-00686-3","DOIUrl":null,"url":null,"abstract":"<p><p>Information systems have to deal with an increasing amount of data that is heterogeneous, unstructured, or incomplete. In order to align and complete data, systems may rely on taxonomies and background knowledge that are provided in the form of an ontology. This survey gives an overview of research work on the use of ontologies for accessing incomplete and/or heterogeneous data.</p>","PeriodicalId":45413,"journal":{"name":"Kunstliche Intelligenz","volume":"34 3","pages":"329-353"},"PeriodicalIF":2.8000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7497697/pdf/","citationCount":"0","resultStr":"{\"title\":\"Ontologies and Data Management: A Brief Survey.\",\"authors\":\"Thomas Schneider, Mantas Šimkus\",\"doi\":\"10.1007/s13218-020-00686-3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Information systems have to deal with an increasing amount of data that is heterogeneous, unstructured, or incomplete. In order to align and complete data, systems may rely on taxonomies and background knowledge that are provided in the form of an ontology. This survey gives an overview of research work on the use of ontologies for accessing incomplete and/or heterogeneous data.</p>\",\"PeriodicalId\":45413,\"journal\":{\"name\":\"Kunstliche Intelligenz\",\"volume\":\"34 3\",\"pages\":\"329-353\"},\"PeriodicalIF\":2.8000,\"publicationDate\":\"2020-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7497697/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Kunstliche Intelligenz\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s13218-020-00686-3\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2020/8/13 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Kunstliche Intelligenz","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s13218-020-00686-3","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2020/8/13 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
Information systems have to deal with an increasing amount of data that is heterogeneous, unstructured, or incomplete. In order to align and complete data, systems may rely on taxonomies and background knowledge that are provided in the form of an ontology. This survey gives an overview of research work on the use of ontologies for accessing incomplete and/or heterogeneous data.
期刊介绍：
Artificial Intelligence has successfully established itself as a scientific discipline in research and education and has become an integral part of Computer Science with an interdisciplinary character. AI deals with both the development of information processing systems that deliver “intelligent” services and with the modeling of human cognitive skills with the help of information processing systems. Research, development and applications in the field of AI pursue the general goal of creating processes for taking in and processing information that more closely resemble human problem-solving behavior, and to subsequently use those processes to derive methods that enhance and qualitatively improve conventional information processing systems. KI – Künstliche Intelligenz is the official journal of the division for artificial intelligence within the ''Gesellschaft für Informatik e.V.'' (GI) – the German Informatics Society – with contributions from the entire field of artificial intelligence. The journal presents fundamentals and tools, their use and adaptation for scientific purposes, and applications that are implemented using AI methods – and thus provides readers with the latest developments in and well-founded background information on all relevant aspects of artificial intelligence. A highly reputed team of editors from both university and industry will ensure the scientific quality of the articles.The journal provides all members of the AI community with quick access to current topics in the field, while also promoting vital interdisciplinary interchange, it will as well serve as a media of communication between the members of the division and the parent society. The journal is published in English. Content published in this journal is peer reviewed (Double Blind).
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