文章基本信息

标题：Incremental Learning: Areas and Methods – A Survey
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作者：Prachi Joshi ; Parag Kulkarni
期刊名称：International Journal of Data Mining & Knowledge Management Process
印刷版ISSN：2231-007X
电子版ISSN：2230-9608
出版年度：2012
卷号：2
期号：5
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：While the areas of applications in data mining are growing substantially, it has become extremely necessary for incremental learning methods to move a step ahead. The tremendous growth of unlabeled data has made incremental learning take up a big leap. Starting from BI applications to image classifications, from analysis to predictions, every domain needs to learn and update. Incremental learning allows to explore new areas at the same time performs knowledge amassing. In this paper we discuss the areas and methods of incremental learning currently taking place and highlight its potentials in aspect of decision making. The paper essentially gives an overview of the current research that will provide a background for the students and research scholars about the topic.
关键词：Incremental; learning; mining; supervised; unsupervised; decision-making