| 書目名稱 | Logical and Relational Learning |
| 編輯 | Luc De Raedt |
| 視頻video | http://file.papertrans.cn/589/588167/588167.mp4 |
| 概述 | First textbook on multirelational data mining and inductive logic programming.Includes supplementary material: |
| 叢書名稱 | Cognitive Technologies |
| 圖書封面 |  |
| 描述 | Iusethetermlogicalandrelationallearning torefertothesub?eldofarti?cial intelligence,machinelearninganddataminingthatisconcernedwithlearning in expressive logical or relational representations. It is the union of inductive logic programming, (statistical) relational learning and multi-relational data mining, which all have contributed techniques for learning from data in re- tional form. Even though some early contributions to logical and relational learning are about forty years old now, it was only with the advent of - ductive logic programming in the early 1990s that the ?eld became popular. Whereas initial work was often concerned with logical (or logic programming) issues,thefocushasrapidlychangedtothediscoveryofnewandinterpretable knowledge from structured data, often in the form of rules, and soon imp- tant successes in applications in domains such as bio- and chemo-informatics and computational linguistics were realized. Today, the challenges and opp- tunities of dealing with structured data and knowledge have been taken up by the arti?cial intelligence community at large and form the motivation for a lot of ongoing research. Indeed, graph, network and multi-relational data |
| 出版日期 | Textbook 2008 |
| 關鍵詞 | artificial intelligence; data mining; database; intelligence; learning; machine learning; programming; rela |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-540-68856-3 |
| isbn_softcover | 978-3-642-05748-9 |
| isbn_ebook | 978-3-540-68856-3Series ISSN 1611-2482 Series E-ISSN 2197-6635 |
| issn_series | 1611-2482 |
| copyright | Springer-Verlag Berlin Heidelberg 2008 |
|Archiver|手機版|小黑屋|
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