A Robust Approach to Schema Matching overWeb Query Interfaces

Jin Pei, Jun Hong, D. Bell
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引用次数: 11

Abstract

In recent years, more and more data sources are available on the Web, where data can be accessed only via web interfaces. To make these data sources sharable, holistic schema matching which benefits from a large number of schemas has attracted much attention. However, current holistic approaches still suffer from the following limitations: a). They are sensitive to noisy data; b). While different types of information about attributes (e.g. attribute names, text descriptions, domain values) have been used, it remains an issue to effectively merge these types of information. In this paper, we propose a re-sampling method for handling noisy data across multiple web interfaces in the same domain. Furthermore, we propose a novel method to utilize different types of information about attributes, which is robust for resolving homonyms. Our experimental results show that our proposed methods are highly effective.
基于web查询接口的模式匹配鲁棒方法
近年来,越来越多的数据源在Web上可用,数据只能通过Web接口访问。为了使这些数据源具有可共享性,得益于大量模式的整体模式匹配备受关注。然而,目前的整体方法仍然存在以下局限性:a)对噪声数据敏感;b).虽然使用了不同类型的属性信息(如属性名称、文本描述、域值),但如何有效地合并这些类型的信息仍然是一个问题。在本文中,我们提出了一种重采样方法来处理同一域中多个web接口的噪声数据。此外,我们提出了一种利用不同类型的属性信息的新方法,该方法对同音异义词的解析具有鲁棒性。实验结果表明,本文提出的方法是非常有效的。
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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