文章基本信息

标题：EXPLOITING UNLABELED DATA IN CONCEPT DRIFT LEARNING
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作者：Dwi Hendratmo Widyantoro
期刊名称：Jurnal Informatika
印刷版ISSN：1411-0105
出版年度：2007
卷号：8
期号：1
页码：pp. 54-62
DOI：10.9744/informatika.8.1.pp. 54-62
语种：English
出版社：Institute of Research and Community Outreach - Petra Christian University
摘要：Learning unlabeled data in a drifting environment still receives little attention. This paper presents a concept tracker algorithm for learning concept drift that exploits unlabeled data. In the absence of complete labeled data, instance classes are identified using a concept hierarchy that is incrementally constructed from data stream (mostly unlabeled data) in unsupervised mode. The persistence assumption in temporal reasoning is then applied to infer target concepts. Empirical evaluation that has been conducted on information-filtering domains demonstrates the effectiveness of this approach.
关键词：concept drift learning, unlabeled data, persistence assumption.