| 书目名称 | Knowledge Discovery in Inductive Databases | | 副标题 | 4th International Wo | | 编辑 | Francesco Bonchi,Jean-François Boulicaut | | 视频video | | | 丛书名称 | Lecture Notes in Computer Science | | 图书封面 |  | | 描述 | The4thInternationalWorkshoponKnowledgeDiscoveryinInductiveDatabases (KDID 2005) was held in Porto, Portugal, on October 3, 2005 in conjunction with the 16th European Conference on Machine Learning and the 9th European Conference on Principles and Practice of Knowledge Discovery in Databases. Ever since the start of the ?eld of data mining, it has been realized that the integration of the database technology into knowledge discovery processes was a crucial issue. This vision has been formalized into the inductive database perspective introduced by T. Imielinski and H. Mannila (CACM 1996, 39(11)). The main idea is to consider knowledge discovery as an extended querying p- cess for which relevant query languages are to be speci?ed. Therefore, inductive databases might contain not only the usual data but also inductive gener- izations (e. g. , patterns, models) holding within the data. Despite many recent developments, there is still a pressing need to understand the central issues in inductive databases. Constraint-based mining has been identi?ed as a core technology for inductive querying, and promising results have been obtained for rather simple types of patterns (e. g. , itemsets, | | 出版日期 | Conference proceedings 2006 | | 关键词 | algorithms; classification; clustering; constraint-based mining; data management; data mining; database; in | | 版次 | 1 | | doi | https://doi.org/10.1007/11733492 | | isbn_softcover | 978-3-540-33292-3 | | isbn_ebook | 978-3-540-33293-0Series ISSN 0302-9743 Series E-ISSN 1611-3349 | | issn_series | 0302-9743 | | copyright | Springer-Verlag Berlin Heidelberg 2006 |
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发表于 2025-3-21 19:51:07
