Toward XML-based knowledge discovery systems

Rosa Meo, G. Psaila
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引用次数: 18

Abstract

Inductive databases are intended to be general purpose databases in which both source data and mined patterns can be represented, retrieved and manipulated. However, the heterogeneity of models for mined patterns makes difficult to realize them. In this paper, we explore the feasibility of using XML as the unifying framework for inductive databases, introducing a suitable data model called XDM (XML for data mining). XDM is designed to describe source raw data, heterogeneous mined patterns and data mining statements, so that they can be stored inside a unique XML-based inductive database.
面向基于xml的知识发现系统
归纳数据库旨在成为通用数据库,源数据和挖掘模式都可以在其中表示、检索和操作。然而,挖掘模式模型的异构性使其难以实现。在本文中,我们探讨了使用XML作为归纳数据库统一框架的可行性,引入了一种合适的数据模型,称为XDM (XML for data mining)。XDM旨在描述源原始数据、异构挖掘模式和数据挖掘语句,以便将它们存储在唯一的基于xml的归纳数据库中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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