Towards building a MetaQuerier: extracting and matching Web query interfaces

Bin He, Zhen Zhang, K. Chang
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引用次数: 16

Abstract

We witness the rapid growth and thus the prevalence of databases on the Web. Our recent study in April 2004 estimated 450,000 online databases. On this deep Web, myriad databases provide dynamic query-based data access through their query interfaces, instead of static URL links. It is thus essential to integrate these query interfaces for integrating the deep Web. The overall goal of the MetaQuerier project aims at opening up the deep Web to users, by building a system to help users exploring and integrating deep Web sources. In particular, to start with, we focus on the integration of deep Web sources in the same domain, which is itself an important integration task. To automate this integration scenario, we need to solve two critical problems: extracting query interfaces and matching query interfaces. To solve the interface extraction problem, we introduce a parsing paradigm by hypothesizing the existence of hidden syntax which describes the layout and semantic of Web interfaces. Also, unlike traditional pairwise schema matching, we propose a holistic matching approach, which matches all schemas at the same time with the hypothesis of a hidden schema model. Therefore, our techniques explore, in essence, "data mining for information integration." That is, we mine the observable information to discover the underlying semantics.
构建一个元查询器:提取和匹配Web查询接口
我们见证了Web上数据库的快速增长和普及。我们最近在2004年4月的研究估计有45万个在线数据库。在这个深度网络上,无数数据库通过查询接口提供动态的基于查询的数据访问,而不是静态的URL链接。因此,整合这些查询接口以整合深度网络是必要的。MetaQuerier项目的总体目标是通过建立一个系统来帮助用户探索和整合深度网络资源,从而向用户开放深度网络。特别是,首先,我们将重点放在同一领域的深度Web源的集成上,这本身就是一项重要的集成任务。为了自动化这个集成场景,我们需要解决两个关键问题:提取查询接口和匹配查询接口。为了解决接口抽取问题,我们通过假设存在描述Web接口布局和语义的隐藏语法,引入了一种解析范式。此外,与传统的两两模式匹配不同,我们提出了一种整体匹配方法,该方法在隐含模式模型的假设下同时匹配所有模式。因此,我们的技术在本质上探索“用于信息集成的数据挖掘”。也就是说,我们挖掘可观察信息来发现底层语义。
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