Advances in Intelligent Data Analysis XVIII
18th International Symposium on Intelligent Data Analysis, IDA 2020, Konstanz, Germany, April 27–29, 2020, Proceedings
dc.contributor.editor | Berthold, Michael | |
dc.contributor.editor | Feelders, Ad | |
dc.contributor.editor | Krempl, Georg | |
dc.date.accessioned | 2020-05-13T14:21:44Z | |
dc.date.available | 2020-05-13T14:21:44Z | |
dc.date.issued | 2020 | |
dc.identifier | ONIX_20200513_9783030445843_20 | |
dc.identifier.uri | http://library.oapen.org/handle/20.500.12657/37720 | |
dc.description.abstract | This open access book constitutes the proceedings of the 18th International Conference on Intelligent Data Analysis, IDA 2020, held in Konstanz, Germany, in April 2020. The 45 full papers presented in this volume were carefully reviewed and selected from 114 submissions. Advancing Intelligent Data Analysis requires novel, potentially game-changing ideas. IDA’s mission is to promote ideas over performance: a solid motivation can be as convincing as exhaustive empirical evaluation. | |
dc.language | English | |
dc.relation.ispartofseries | Lecture Notes in Computer Science; Information Systems and Applications, incl. Internet/Web, and HCI | |
dc.subject.classification | thema EDItEUR::U Computing and Information Technology::UN Databases | en_US |
dc.subject.classification | thema EDItEUR::U Computing and Information Technology::UN Databases::UNF Data mining | en_US |
dc.subject.classification | thema EDItEUR::U Computing and Information Technology::UB Information technology: general topics | en_US |
dc.subject.classification | thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning | en_US |
dc.subject.classification | thema EDItEUR::U Computing and Information Technology::UT Computer networking and communications | en_US |
dc.subject.other | Database Management | |
dc.subject.other | Data Mining and Knowledge Discovery | |
dc.subject.other | Computing Milieux | |
dc.subject.other | Machine Learning | |
dc.subject.other | Computer Systems Organization and Communication Networks | |
dc.subject.other | open access | |
dc.subject.other | data mining | |
dc.subject.other | learning systems | |
dc.subject.other | classification | |
dc.subject.other | clustering | |
dc.subject.other | semantics | |
dc.subject.other | learning algorithms | |
dc.subject.other | supervised learning | |
dc.subject.other | association rules | |
dc.subject.other | social networks | |
dc.subject.other | graphic methods | |
dc.subject.other | neural networks | |
dc.subject.other | artificial intelligence | |
dc.subject.other | computer vision | |
dc.subject.other | correlation analysis | |
dc.subject.other | databases | |
dc.subject.other | education | |
dc.subject.other | engineering | |
dc.subject.other | graph theory | |
dc.subject.other | image analysis | |
dc.subject.other | Databases | |
dc.subject.other | Database programming | |
dc.subject.other | Data mining | |
dc.subject.other | Expert systems / knowledge-based systems | |
dc.subject.other | Information technology: general issues | |
dc.subject.other | Machine learning | |
dc.subject.other | Computer networking & communications | |
dc.title | Advances in Intelligent Data Analysis XVIII | |
dc.title.alternative | 18th International Symposium on Intelligent Data Analysis, IDA 2020, Konstanz, Germany, April 27–29, 2020, Proceedings | |
dc.type | book | |
oapen.identifier.doi | 10.1007/978-3-030-44584-3 | |
oapen.relation.isPublishedBy | 6c6992af-b843-4f46-859c-f6e9998e40d5 | |
oapen.imprint | Springer | |
oapen.series.number | 12080 | |
oapen.pages | 588 | |
oapen.place.publication | Cham |